Senior Data Scientist Welwyn Garden City, Hertfordshire or Slough, Berkshire | Hybrid (2 Days Office) | Python | SQL | PySpark | Azure | Databricks | Machine Learning | Statistics | Time Series Forecasting | Propensity Models Role: Senior Data Scientist, Lead Data Scientist, ML Scientist, AI Data Scientist, Statistical Data Scientist, Predictive Analytics Key Skills: Senior Data Scientist, Data Scientist, Machine Learning, Artificial Intelligence, Predictive Analytics, Statistical Modelling, Python, SQL, PySpark, Azure, Databricks, MLflow, GitHub Actions, CI/CD, Time Series Forecasting, Propensity Modelling, Feature Engineering, Data Engineering, Azure Machine Learning, Azure Data Platform, Experiment Design, A/B Testing, Hypothesis Testing, Predictive Modelling, Customer Analytics, Marketing Analytics, Customer Lifetime Value, Churn Prediction, Demand Forecasting, Stock Forecasting, Production Machine Learning, Cloud Data Platforms, Data Products, Git, Version Control, MLOps, Data Pipelines. Location: Hybrid role. 2 days per week in office Either: Welwyn Garden City, Hertfordshire or Slough, Berkshire Type: Permanent | Full-Time Overview: is recruiting for an experienced Senior Data Scientist to join one of the UK's most advanced Data Science teams, helping shape the future of customer analytics through cutting-edge machine learning, statistical modelling & cloud-based AI solutions. This is a great opportunity for an experienced Data Scientist who enjoys solving complex commercial problems using advanced analytics, statistical modelling & machine learning techniques, whilst delivering production-ready data science solutions that directly influence customer experience & business performance. This position offers exposure to large-scale customer datasets, advanced Azure-based technologies & highly collaborative multidisciplinary teams consisting of Data Scientists, Data Engineers & Data Analysts. Purpose: Design, develop & deploy enterprise-scale data science solutions that improve customer outcomes, enhance commercial performance & support strategic business decision making. Own the complete analytical life cycle, from initial problem definition & exploratory analysis through feature engineering, model development, deployment, operational monitoring & continuous optimisation. Build sophisticated statistical & machine learning models covering areas such as: * Customer Lifetime Value * Customer Propensity Modelling * Customer Churn Prediction * Marketing Optimisation * Personalisation * Time Series Forecasting * Stock Forecasting * Demand Planning * Customer Behaviour Analytics * Decision Intelligence Technology Stack: Programming * Python * SQL * PySpark Cloud & Platforms * Microsoft Azure * Azure Databricks * Azure Machine Learning Machine Learning & AI * Statistical Modelling * Predictive Analytics * Feature Engineering * Propensity Modelling * Time Series Forecasting * MLflow * PyTorch Data Engineering * Data Pipelines * Graph Databases DevOps & Development * GitHub * GitHub Actions * CI/CD * Version Control Core Activity: * Deliver end-to-end data science solutions from concept to production * Build machine learning models that improve customer & business outcomes * Apply statistical techniques to solve complex business problems * Develop propensity & predictive models for customer decisioning * Design & optimise time series forecasting models * Build scalable data pipelines & production-ready analytics * Collaborate with cross-functional teams to deliver business value * Monitor, maintain & continuously improve deployed models * Present analytical insights to technical & business stakeholders * Promote best practice in data science & software engineering Responsibilities: * Take ownership of the complete data science life cycle, including problem definition, exploratory data analysis, feature engineering, model development, validation, deployment & ongoing optimisation. * Design & execute statistically rigorous analytical approaches, including hypothesis testing, experimental design, uncertainty measurement & business impact assessment. * Develop sophisticated propensity models to support customer targeting, customer engagement, personalisation & commercial decision making. * Build highly accurate time series forecasting models covering both customer demand & stock forecasting, continuously improving forecast performance through back-testing & model refinement. * Develop scalable, production-ready machine learning solutions using Python, SQL & PySpark within Azure Databricks. * Build, optimise & maintain robust data pipelines using software engineering best practices, including automated testing, documentation, version control & reproducibility. * Work closely with stakeholders to understand business challenges, define measurable success criteria & translate analytical outputs into commercially valuable recommendations. * Monitor model performance, identify opportunities for optimisation & continuously improve deployed solutions. * Conduct peer reviews of analytical code & statistical models, helping to raise technical standards across the wider Data Science function. * Promote best practice in machine learning, statistical modelling, software engineering & cloud-based analytics delivery. Deliverables: * Production-ready machine learning models * Customer propensity models * Time series forecasting solutions * Actionable business insights * Scalable, secure machine learning code * Azure-based data pipelines * Stakeholder reports & recommendations * Optimised model performance * Well-documented analytical solutions * Successful cross-functional delivery Working Environment: * Hybrid Working * Agile Delivery * Azure Cloud Platform * Azure Databricks * Cross-Functional Product Squads * Enterprise Data Science * Large-Scale Data Environment * CI/CD & DevOps * Continuous Learning & Innovation Candidate Profile: Candidates should possess experience as a Senior Data Scientist with strong analytical skills, commercial awareness & a passion for solving complex business problems. You'll have a proven track record of delivering end-to-end data science solutions, from problem definition through to production deployment, using advanced statistics, machine learning & cloud technologies. You'll be confident working with both structured & time series data, building scalable models that deliver measurable business value. Your experience is likely to include some of the following: Essential: * End-to-end data science delivery * Statistical modelling & hypothesis testing * Machine learning & predictive analytics * Propensity modelling * Time series forecasting * Python * SQL * PySpark * Microsoft Azure Cloud * Azure Databricks * Feature engineering * Production ML deployment * Version control & automated testing * Data integration & modelling * Stakeholder management * Agile delivery experience Desirable: * MLflow * PyTorch * Databricks Asset Bundles * Graph Databases * Azure Machine Learning * GitHub Actions * CI/CD * MLOps * Marketing Analytics * Customer Lifetime Value (CLV) * Churn Prediction * Retail Analytics * Customer Personalisation * Decision Intelligence Key Traits: * Curious & analytical * Commercially minded * Customer focused * Strong statistical thinking * Detail orientated * Excellent communicator * Adaptable & delivery focused : uniting opportunity with ambition in Telecoms | Media | Technology is the brand name of MECS Communications Ltd who provide permanent & contract recruitment consultancy service as an Employment Agency & Employment Business.
28/07/2026
Full time
Senior Data Scientist Welwyn Garden City, Hertfordshire or Slough, Berkshire | Hybrid (2 Days Office) | Python | SQL | PySpark | Azure | Databricks | Machine Learning | Statistics | Time Series Forecasting | Propensity Models Role: Senior Data Scientist, Lead Data Scientist, ML Scientist, AI Data Scientist, Statistical Data Scientist, Predictive Analytics Key Skills: Senior Data Scientist, Data Scientist, Machine Learning, Artificial Intelligence, Predictive Analytics, Statistical Modelling, Python, SQL, PySpark, Azure, Databricks, MLflow, GitHub Actions, CI/CD, Time Series Forecasting, Propensity Modelling, Feature Engineering, Data Engineering, Azure Machine Learning, Azure Data Platform, Experiment Design, A/B Testing, Hypothesis Testing, Predictive Modelling, Customer Analytics, Marketing Analytics, Customer Lifetime Value, Churn Prediction, Demand Forecasting, Stock Forecasting, Production Machine Learning, Cloud Data Platforms, Data Products, Git, Version Control, MLOps, Data Pipelines. Location: Hybrid role. 2 days per week in office Either: Welwyn Garden City, Hertfordshire or Slough, Berkshire Type: Permanent | Full-Time Overview: is recruiting for an experienced Senior Data Scientist to join one of the UK's most advanced Data Science teams, helping shape the future of customer analytics through cutting-edge machine learning, statistical modelling & cloud-based AI solutions. This is a great opportunity for an experienced Data Scientist who enjoys solving complex commercial problems using advanced analytics, statistical modelling & machine learning techniques, whilst delivering production-ready data science solutions that directly influence customer experience & business performance. This position offers exposure to large-scale customer datasets, advanced Azure-based technologies & highly collaborative multidisciplinary teams consisting of Data Scientists, Data Engineers & Data Analysts. Purpose: Design, develop & deploy enterprise-scale data science solutions that improve customer outcomes, enhance commercial performance & support strategic business decision making. Own the complete analytical life cycle, from initial problem definition & exploratory analysis through feature engineering, model development, deployment, operational monitoring & continuous optimisation. Build sophisticated statistical & machine learning models covering areas such as: * Customer Lifetime Value * Customer Propensity Modelling * Customer Churn Prediction * Marketing Optimisation * Personalisation * Time Series Forecasting * Stock Forecasting * Demand Planning * Customer Behaviour Analytics * Decision Intelligence Technology Stack: Programming * Python * SQL * PySpark Cloud & Platforms * Microsoft Azure * Azure Databricks * Azure Machine Learning Machine Learning & AI * Statistical Modelling * Predictive Analytics * Feature Engineering * Propensity Modelling * Time Series Forecasting * MLflow * PyTorch Data Engineering * Data Pipelines * Graph Databases DevOps & Development * GitHub * GitHub Actions * CI/CD * Version Control Core Activity: * Deliver end-to-end data science solutions from concept to production * Build machine learning models that improve customer & business outcomes * Apply statistical techniques to solve complex business problems * Develop propensity & predictive models for customer decisioning * Design & optimise time series forecasting models * Build scalable data pipelines & production-ready analytics * Collaborate with cross-functional teams to deliver business value * Monitor, maintain & continuously improve deployed models * Present analytical insights to technical & business stakeholders * Promote best practice in data science & software engineering Responsibilities: * Take ownership of the complete data science life cycle, including problem definition, exploratory data analysis, feature engineering, model development, validation, deployment & ongoing optimisation. * Design & execute statistically rigorous analytical approaches, including hypothesis testing, experimental design, uncertainty measurement & business impact assessment. * Develop sophisticated propensity models to support customer targeting, customer engagement, personalisation & commercial decision making. * Build highly accurate time series forecasting models covering both customer demand & stock forecasting, continuously improving forecast performance through back-testing & model refinement. * Develop scalable, production-ready machine learning solutions using Python, SQL & PySpark within Azure Databricks. * Build, optimise & maintain robust data pipelines using software engineering best practices, including automated testing, documentation, version control & reproducibility. * Work closely with stakeholders to understand business challenges, define measurable success criteria & translate analytical outputs into commercially valuable recommendations. * Monitor model performance, identify opportunities for optimisation & continuously improve deployed solutions. * Conduct peer reviews of analytical code & statistical models, helping to raise technical standards across the wider Data Science function. * Promote best practice in machine learning, statistical modelling, software engineering & cloud-based analytics delivery. Deliverables: * Production-ready machine learning models * Customer propensity models * Time series forecasting solutions * Actionable business insights * Scalable, secure machine learning code * Azure-based data pipelines * Stakeholder reports & recommendations * Optimised model performance * Well-documented analytical solutions * Successful cross-functional delivery Working Environment: * Hybrid Working * Agile Delivery * Azure Cloud Platform * Azure Databricks * Cross-Functional Product Squads * Enterprise Data Science * Large-Scale Data Environment * CI/CD & DevOps * Continuous Learning & Innovation Candidate Profile: Candidates should possess experience as a Senior Data Scientist with strong analytical skills, commercial awareness & a passion for solving complex business problems. You'll have a proven track record of delivering end-to-end data science solutions, from problem definition through to production deployment, using advanced statistics, machine learning & cloud technologies. You'll be confident working with both structured & time series data, building scalable models that deliver measurable business value. Your experience is likely to include some of the following: Essential: * End-to-end data science delivery * Statistical modelling & hypothesis testing * Machine learning & predictive analytics * Propensity modelling * Time series forecasting * Python * SQL * PySpark * Microsoft Azure Cloud * Azure Databricks * Feature engineering * Production ML deployment * Version control & automated testing * Data integration & modelling * Stakeholder management * Agile delivery experience Desirable: * MLflow * PyTorch * Databricks Asset Bundles * Graph Databases * Azure Machine Learning * GitHub Actions * CI/CD * MLOps * Marketing Analytics * Customer Lifetime Value (CLV) * Churn Prediction * Retail Analytics * Customer Personalisation * Decision Intelligence Key Traits: * Curious & analytical * Commercially minded * Customer focused * Strong statistical thinking * Detail orientated * Excellent communicator * Adaptable & delivery focused : uniting opportunity with ambition in Telecoms | Media | Technology is the brand name of MECS Communications Ltd who provide permanent & contract recruitment consultancy service as an Employment Agency & Employment Business.
United States Digital Space LLC
Cambridge, Cambridgeshire
C++ AI/ML Software Engineer HP Wolf Security is changing the future of endpoint security through delivering secure PCs with advanced hardware enforced security features. As AI becomes increasingly important in cybersecurity, we are expanding our R&D team in Cambridge, UK and are looking for an experienced C++ AI/ML Software Engineer to help develop the next generation of intelligent security solutions. You will be designing, developing, and optimizing AI and machine learning capabilities within our security platform, contributing to innovative features that leverage advanced analytics, behavioural detection, and intelligent threat prevention. Working as part of a highly collaborative engineering team, you will help bridge the gap between cutting edge machine learning research and production grade security software. To see what our engineering teams are working on, visit our technical blogs: We're looking for a talented software engineer with a strong background in modern C++ development and experience applying machine learning and AI techniques within commercial software products. This is a fantastic full time opportunity for a collaborative, hands on, and experienced developer to join a growing team working at the intersection of cybersecurity, systems software, and artificial intelligence. We offer a comprehensive benefits package and excellent career development opportunities. Responsibilities Design, develop, and maintain AI/ML driven features within HP Wolf Security products. Develop high performance C++ components that integrate machine learning models into endpoint security solutions. Collaborate with data scientists and security researchers to productionise AI and machine learning algorithms. Optimise model inference, performance, scalability, and resource utilisation on endpoint devices. Develop data processing, evaluation, and automation tools using Python. Contribute to the design and implementation of intelligent threat detection, behavioural analysis, and anomaly detection capabilities. Participate in architecture discussions, code reviews, testing, and continuous improvement of engineering practices. Evaluate emerging AI technologies and contribute to future product innovation. Qualifications Strong proficiency in modern C++ design, development, debugging, testing, and performance optimisation. Experience developing and deploying machine learning or AI based software solutions. Excellent analytical, problem solving, and software engineering skills. Experience working with Python for machine learning workflows, automation, or tooling. Understanding of software development lifecycle, testing methodologies, and version control systems. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or equivalent experience. Desired Additional Experience Machine learning frameworks such as TensorFlow, PyTorch, ONNX Runtime, or similar. AI model deployment, optimisation, and inference in production environments. Data processing, feature engineering, and model evaluation techniques. Security, cybersecurity, or threat detection applications of AI/ML. Large Language Models (LLMs), Generative AI, or AI assisted security technologies. High performance, multi threaded, or systems level C++ development. Cloud based AI/ML services and MLOps practices. Location & Working Model This role is based in HP's Cambridge office under a hybrid working arrangement, with a minimum requirement to be onsite three days per week. As a people focused senior role, regular in person collaboration is encouraged. About You You're out to reimagine and reinvent what's possible - in your career as well as the world around you. We love taking on tough challenges, disrupting the status quo, and creating what's next. We're in search of talented people who are inspired by big challenges, driven to learn and grow, and dedicated to making a meaningful difference. Why Join HP Wolf Security HP Wolf Security is central to HP's strategy in the PC market, with security designed into hardware, firmware, and software. This integrated approach enables HP to differentiate through built in, enterprise grade protection and manageability. This role sits at the heart of that strategy, helping deliver the tools that allow customers to deploy, manage, and trust secure PCs at scale. The primary focus of the HP Wolf Security team is developing cyber security solutions to protect our customers' devices and data. The digital threat landscape is ever changing and as the cybersecurity industry reacts and adapts to changes, so too do the malware authors. Our unique micro virtualization technology ensures customers are protected from even the most bleeding edge cyber security threats. That micro virtualization technology forms a key pillar in a wider cyber security suite that we're actively developing. Our History Inspired by the isolation principles of traditional virtualization, HP's team known then as Bromium created a game changing technology called micro virtualization to protect end users against advanced malware. Every task the user performs, such as opening a document or clicking on a link, is isolated in its own micro VM, with access to just the resources required for that task, and existing just for the life of the task. Protection is thus provided through isolation, without relying on detection, hence reliably defending the user from polymorphic and even zero day malware. Bromium was acquired by HP Inc on 19 September 2019 forming HP Wolf Security. For more information, visit our website: Equal Opportunity Employer (EEO) HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation, or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: "Know Your Rights: Workplace Discrimination is Illegal".
27/07/2026
Full time
C++ AI/ML Software Engineer HP Wolf Security is changing the future of endpoint security through delivering secure PCs with advanced hardware enforced security features. As AI becomes increasingly important in cybersecurity, we are expanding our R&D team in Cambridge, UK and are looking for an experienced C++ AI/ML Software Engineer to help develop the next generation of intelligent security solutions. You will be designing, developing, and optimizing AI and machine learning capabilities within our security platform, contributing to innovative features that leverage advanced analytics, behavioural detection, and intelligent threat prevention. Working as part of a highly collaborative engineering team, you will help bridge the gap between cutting edge machine learning research and production grade security software. To see what our engineering teams are working on, visit our technical blogs: We're looking for a talented software engineer with a strong background in modern C++ development and experience applying machine learning and AI techniques within commercial software products. This is a fantastic full time opportunity for a collaborative, hands on, and experienced developer to join a growing team working at the intersection of cybersecurity, systems software, and artificial intelligence. We offer a comprehensive benefits package and excellent career development opportunities. Responsibilities Design, develop, and maintain AI/ML driven features within HP Wolf Security products. Develop high performance C++ components that integrate machine learning models into endpoint security solutions. Collaborate with data scientists and security researchers to productionise AI and machine learning algorithms. Optimise model inference, performance, scalability, and resource utilisation on endpoint devices. Develop data processing, evaluation, and automation tools using Python. Contribute to the design and implementation of intelligent threat detection, behavioural analysis, and anomaly detection capabilities. Participate in architecture discussions, code reviews, testing, and continuous improvement of engineering practices. Evaluate emerging AI technologies and contribute to future product innovation. Qualifications Strong proficiency in modern C++ design, development, debugging, testing, and performance optimisation. Experience developing and deploying machine learning or AI based software solutions. Excellent analytical, problem solving, and software engineering skills. Experience working with Python for machine learning workflows, automation, or tooling. Understanding of software development lifecycle, testing methodologies, and version control systems. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or equivalent experience. Desired Additional Experience Machine learning frameworks such as TensorFlow, PyTorch, ONNX Runtime, or similar. AI model deployment, optimisation, and inference in production environments. Data processing, feature engineering, and model evaluation techniques. Security, cybersecurity, or threat detection applications of AI/ML. Large Language Models (LLMs), Generative AI, or AI assisted security technologies. High performance, multi threaded, or systems level C++ development. Cloud based AI/ML services and MLOps practices. Location & Working Model This role is based in HP's Cambridge office under a hybrid working arrangement, with a minimum requirement to be onsite three days per week. As a people focused senior role, regular in person collaboration is encouraged. About You You're out to reimagine and reinvent what's possible - in your career as well as the world around you. We love taking on tough challenges, disrupting the status quo, and creating what's next. We're in search of talented people who are inspired by big challenges, driven to learn and grow, and dedicated to making a meaningful difference. Why Join HP Wolf Security HP Wolf Security is central to HP's strategy in the PC market, with security designed into hardware, firmware, and software. This integrated approach enables HP to differentiate through built in, enterprise grade protection and manageability. This role sits at the heart of that strategy, helping deliver the tools that allow customers to deploy, manage, and trust secure PCs at scale. The primary focus of the HP Wolf Security team is developing cyber security solutions to protect our customers' devices and data. The digital threat landscape is ever changing and as the cybersecurity industry reacts and adapts to changes, so too do the malware authors. Our unique micro virtualization technology ensures customers are protected from even the most bleeding edge cyber security threats. That micro virtualization technology forms a key pillar in a wider cyber security suite that we're actively developing. Our History Inspired by the isolation principles of traditional virtualization, HP's team known then as Bromium created a game changing technology called micro virtualization to protect end users against advanced malware. Every task the user performs, such as opening a document or clicking on a link, is isolated in its own micro VM, with access to just the resources required for that task, and existing just for the life of the task. Protection is thus provided through isolation, without relying on detection, hence reliably defending the user from polymorphic and even zero day malware. Bromium was acquired by HP Inc on 19 September 2019 forming HP Wolf Security. For more information, visit our website: Equal Opportunity Employer (EEO) HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation, or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: "Know Your Rights: Workplace Discrimination is Illegal".
AI Solution Architect - Senior Manager/Associate Director Capital Markets Location: London Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13117 Senior AI Solution Architects are required to support the design, implementation and scaling of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI, cloud and data architecture, with experience designing enterprise AI solutions and translating business requirements into scalable technical architectures. You will play a key role in shaping AI architecture strategy, leading technical teams and supporting organisations as they move from strategy and experimentation through to enterprise deployment. You will work closely with AI Engineers, Data Scientists, Enterprise Architects, MLOps teams, business stakeholders and senior leadership to design, deliver and scale AI solutions that drive measurable business outcomes. Key responsibilities: Translating business objectives into AI architecture strategies, roadmaps and scalable solution designs Designing and implementing end to end AI and ML architectures across enterprise environments Defining scalable, performant and cost optimised deployment patterns across cloud, containerised and GPU enabled environments Supporting AI implementation programmes from proof of concept through to enterprise deployment and optimisation Evaluating and selecting technologies across open source and commercial platforms Designing and integrating AI solutions into existing enterprise systems and applications Working with AI Engineers, Data Scientists and technical teams to support AI delivery and scaling initiatives Supporting AI governance, security, risk and regulatory considerations throughout the delivery lifecycle Supporting architecture governance, technical review boards and design authorities Building relationships with technical and business stakeholders across large scale transformation programmes Producing solution design documentation, implementation plans and technical proposals Providing technical leadership and mentoring within multidisciplinary teams Experience Required: Experience designing AI, ML or modern data architectures within enterprise environments Strong understanding of cloud platforms such as AWS, Azure, GCP, Databricks or similar technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience designing APIs and integrating AI solutions into enterprise environments Strong understanding of modern data architectures and platform design principles Experience presenting architectural designs to technical and business stakeholders Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI architecture professional who wants to work on high impact AI and data transformation programmes within complex financial services environments. For more information make an application today! Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme. Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data UK. For more information visit our website: (url removed)
27/07/2026
Full time
AI Solution Architect - Senior Manager/Associate Director Capital Markets Location: London Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13117 Senior AI Solution Architects are required to support the design, implementation and scaling of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI, cloud and data architecture, with experience designing enterprise AI solutions and translating business requirements into scalable technical architectures. You will play a key role in shaping AI architecture strategy, leading technical teams and supporting organisations as they move from strategy and experimentation through to enterprise deployment. You will work closely with AI Engineers, Data Scientists, Enterprise Architects, MLOps teams, business stakeholders and senior leadership to design, deliver and scale AI solutions that drive measurable business outcomes. Key responsibilities: Translating business objectives into AI architecture strategies, roadmaps and scalable solution designs Designing and implementing end to end AI and ML architectures across enterprise environments Defining scalable, performant and cost optimised deployment patterns across cloud, containerised and GPU enabled environments Supporting AI implementation programmes from proof of concept through to enterprise deployment and optimisation Evaluating and selecting technologies across open source and commercial platforms Designing and integrating AI solutions into existing enterprise systems and applications Working with AI Engineers, Data Scientists and technical teams to support AI delivery and scaling initiatives Supporting AI governance, security, risk and regulatory considerations throughout the delivery lifecycle Supporting architecture governance, technical review boards and design authorities Building relationships with technical and business stakeholders across large scale transformation programmes Producing solution design documentation, implementation plans and technical proposals Providing technical leadership and mentoring within multidisciplinary teams Experience Required: Experience designing AI, ML or modern data architectures within enterprise environments Strong understanding of cloud platforms such as AWS, Azure, GCP, Databricks or similar technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience designing APIs and integrating AI solutions into enterprise environments Strong understanding of modern data architectures and platform design principles Experience presenting architectural designs to technical and business stakeholders Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI architecture professional who wants to work on high impact AI and data transformation programmes within complex financial services environments. For more information make an application today! Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme. Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data UK. For more information visit our website: (url removed)
Senior AI Engineer Manager/Associate Director Capital Markets Location: London Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13114 Senior AI Engineering professionals are required to support the design, build and delivery of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI engineering and enterprise solution delivery within complex environments. You will play a key role in shaping AI strategy, leading teams and delivering enterprise AI solutions, helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building and deploying AI prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting AI deployment, serving patterns, evaluation frameworks and integration design Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data privacy and regulatory risks Contributing to technical documentation, solution design and delivery planning Supporting AI implementation and scaling initiatives across complex environments Leading and developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing or supporting evaluation frameworks for AI or agentic systems Experience working with modern data architectures and cloud platforms Understanding of AI risk, governance, security and regulatory considerations Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI engineering professional who wants to work on high impact AI and data transformation programmes within complex financial services environments. Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme. Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data UK. For more information visit our website: (url removed)
27/07/2026
Full time
Senior AI Engineer Manager/Associate Director Capital Markets Location: London Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13114 Senior AI Engineering professionals are required to support the design, build and delivery of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI engineering and enterprise solution delivery within complex environments. You will play a key role in shaping AI strategy, leading teams and delivering enterprise AI solutions, helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building and deploying AI prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting AI deployment, serving patterns, evaluation frameworks and integration design Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data privacy and regulatory risks Contributing to technical documentation, solution design and delivery planning Supporting AI implementation and scaling initiatives across complex environments Leading and developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing or supporting evaluation frameworks for AI or agentic systems Experience working with modern data architectures and cloud platforms Understanding of AI risk, governance, security and regulatory considerations Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI engineering professional who wants to work on high impact AI and data transformation programmes within complex financial services environments. Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme. Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data UK. For more information visit our website: (url removed)
Senior Data Scientist Location: London (Hybrid) | Practice Area : Data & Analytics | Type: Permanent Shape intelligent solutions. Lead with insight. Drive data innovation. The Role We are looking for a Senior Data Scientist to join Capco's growing UK Data Practice. You will play a leading role in designing and implementing cutting-edge data science solutions across financial services. This is an opportunity to build intelligent systems that drive commercial and customer outcomes - while mentoring others and collaborating in a dynamic, multi-disciplinary environment. What You'll Do Lead the end-to-end delivery of data science solutions including PoCs, MVPs and production deployments Develop and prototype ML models to solve complex business challenges using modern techniques and tooling Collaborate closely with engineers, domain experts, and business teams to translate requirements into deliverables Guide and coach data science pods, supporting skill development and solution design Act as a subject matter expert on ML architecture, model calibration and productionisation What We're Looking For Hands-on experience building and deploying data science solutions in Python and related ML libraries Strong background in applied machine learning, model development and data engineering Experience with cloud environments (Azure, AWS, GCP) and tools such as Spark, Hive, Redshift Demonstrated ability to lead cross-functional teams and mentor junior practitioners Ability to communicate complex technical concepts clearly to non-technical audiences Bonus Points For Participation in Kaggle or other data science competitions Experience with MLOps practices (CI/CD, model monitoring, DevOps integration) Familiarity with advanced NLP frameworks such as spaCy or Transformers MSc or PhD in a numerate discipline Financial services or banking experience Why Join Capco Deliver high-impact technology solutions for Tier 1 financial institutions Work in a collaborative, flat, and entrepreneurial consulting culture Access continuous learning, training, and industry certifications Be part of a team shaping the future of digital financial services Help shape the future of digital transformation across FS & Energy. We offer a competitive, people-first benefits package designed to support every aspect of your life: Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover. Mental Health: Easy access to CareFirst, Unmind, Aviva consultations and in-house first aiders. Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause and bereavement. Family Care: 8 complimentary backup care sessions for emergency childcare or elder care. Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs. Continuous Learning: Minimum 40 Hours of Training Annually: Take your pick - workshops, certifications, E-learning - your growth, your way. Also, Business Coach assigned from Day One: Get one-on-one guidance to fast-track your goals and accelerate your development. Healthcare Access: Convenient online GP services. Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work and dental insurance. Inclusion at Capco We're committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know - we'll be happy to help. We value each person's unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our culture encourages individuality and collaboration - a mindset that shapes how we work with clients and each other every day.
27/07/2026
Full time
Senior Data Scientist Location: London (Hybrid) | Practice Area : Data & Analytics | Type: Permanent Shape intelligent solutions. Lead with insight. Drive data innovation. The Role We are looking for a Senior Data Scientist to join Capco's growing UK Data Practice. You will play a leading role in designing and implementing cutting-edge data science solutions across financial services. This is an opportunity to build intelligent systems that drive commercial and customer outcomes - while mentoring others and collaborating in a dynamic, multi-disciplinary environment. What You'll Do Lead the end-to-end delivery of data science solutions including PoCs, MVPs and production deployments Develop and prototype ML models to solve complex business challenges using modern techniques and tooling Collaborate closely with engineers, domain experts, and business teams to translate requirements into deliverables Guide and coach data science pods, supporting skill development and solution design Act as a subject matter expert on ML architecture, model calibration and productionisation What We're Looking For Hands-on experience building and deploying data science solutions in Python and related ML libraries Strong background in applied machine learning, model development and data engineering Experience with cloud environments (Azure, AWS, GCP) and tools such as Spark, Hive, Redshift Demonstrated ability to lead cross-functional teams and mentor junior practitioners Ability to communicate complex technical concepts clearly to non-technical audiences Bonus Points For Participation in Kaggle or other data science competitions Experience with MLOps practices (CI/CD, model monitoring, DevOps integration) Familiarity with advanced NLP frameworks such as spaCy or Transformers MSc or PhD in a numerate discipline Financial services or banking experience Why Join Capco Deliver high-impact technology solutions for Tier 1 financial institutions Work in a collaborative, flat, and entrepreneurial consulting culture Access continuous learning, training, and industry certifications Be part of a team shaping the future of digital financial services Help shape the future of digital transformation across FS & Energy. We offer a competitive, people-first benefits package designed to support every aspect of your life: Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover. Mental Health: Easy access to CareFirst, Unmind, Aviva consultations and in-house first aiders. Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause and bereavement. Family Care: 8 complimentary backup care sessions for emergency childcare or elder care. Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs. Continuous Learning: Minimum 40 Hours of Training Annually: Take your pick - workshops, certifications, E-learning - your growth, your way. Also, Business Coach assigned from Day One: Get one-on-one guidance to fast-track your goals and accelerate your development. Healthcare Access: Convenient online GP services. Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work and dental insurance. Inclusion at Capco We're committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know - we'll be happy to help. We value each person's unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our culture encourages individuality and collaboration - a mindset that shapes how we work with clients and each other every day.
White Collar Factory (95009), United Kingdom, London, London Staff Software Engineer - Machine Learning About this role We're on a mission to transform the way we use data and AI to service our customers and drive efficiency across the business. Do you love shaping the technical landscape and driving innovation across the organisation? Are you passionate about solving complex ML and AI challenges and supporting multiple teams toward a shared technical vision? At Capital One, you'll be part of a community of technical leaders who drive engineering excellence, foster innovation, and deliver impactful ML/AI and Gen AI solutions that meet real customer needs. What You'll Do Own and drive the ML/AI technical strategy for UK use cases, spanning multiple teams and influencing the overall technical direction for AI adoption Lead and coordinate ML engineering efforts across multiple teams, ensuring alignment with broader business objectives, enterprise platform capabilities, and technology strategy Provide technical consultancy to teams delivering AI use cases, guiding architectural decisions, solution design, and effective use of enterprise ML/AI platforms and capabilities Proactively identify emerging ML/AI patterns, define and evangelise best practices, and establish reusable approaches that enhance delivery of AI use cases across the business Drive MLOps standards and practices across teams, including CI/CD for models, automated testing, monitoring, and deployment pipelines Collaborate with enterprise platform and data science teams, contributing to platform capabilities where appropriate and partnering on use case delivery Build and maintain strong relationships with key stakeholders, including senior leadership, product owners, data science teams, and enterprise platform partners Represent Capital One in external ML/AI technical forums, contributing to industry discussions Develop and advocate for strategies to proactively manage technical debt across ML/AI systems Actively mentor and develop engineers, fostering a culture of continuous learning What we're looking for Deep expertise in Python and ML engineering Deep expertise in ML/AI systems design, MLOps, and cloud-native architectures Track record of leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems Experience designing and scaling low-latency, customer-facing ML/AI architectures Proven experience setting a multi-team ML/AI technical vision and strategy Strong track record of technical leadership and influence without authority Experience driving ML engineering standards and best practices across organisations Deep understanding of the full ML/AI development lifecycle, including model serving, data pipelines, and Gen AI systems Experience leveraging enterprise platforms to deliver business use cases at scale Experience of steering Communities of Practice or technical forums Strong business acumen and ability to translate ML/AI concepts for various audiences Where and how you'll work This is a permanent position based in our London office. We have a hybrid working model which gives you flexibility to work from our office and from home. We're big on collaboration and connection, so you'll be based in our London office 3 days a week on Tuesdays, Wednesdays and Thursdays. What's in it for you Bring us all this - and you'll be well rewarded with a role contributing to the roadmap of an organisation committed to transformation We offer high performers strong and diverse career progression, investing heavily in developing great people through our Capital One University training programmes (and appropriate external providers) Immediate access to our core benefits including pension scheme, bonus, generous holiday entitlement and private medical insurance - with flexible benefits available including season-ticket loans, cycle to work scheme and enhanced parental leave Open-plan workspaces and accessible facilities designed to inspire and support you. Our Nottingham head-office has a fully-serviced gym, subsidised restaurant, mindfulness and music rooms. What you should know about how we recruit We pride ourselves on hiring the best people, not the same people. Building diverse and inclusive teams is the right thing to do and the smart thing to do. We want to work with top talent: whoever you are, whatever you look like, wherever you come from. We know it's about what you do, not just what you say. That's why we make our recruitment process fair and accessible. And we offer benefits that attract people at all ages and stages. We also partner with organisations including the Women in Finance and Race At Work Charters, Stonewall and upReach to find people from every walk of life and help them thrive with us. We have a whole host of internal networks and support groups you could be involved in, to name a few: REACH - Race Equality and Culture Heritage group focuses on representation, retention and engagement for associates from minority ethnic groups and allies OutFront - to provide LGBTQ+ support for all associates Mind Your Mind - signposting support and promoting positive mental wellbeing for all Women in Tech - promoting an inclusive environment in tech EmpowHER - network of female associates and allies focusing on developing future leaders, particularly for female talent in our industry Enabled - focused on supporting associates with disabilities and neurodiversity Capital One is committed to diversity in the workplace. If you require a reasonable adjustment, please contact All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). Who We Are At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding. Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.
27/07/2026
Full time
White Collar Factory (95009), United Kingdom, London, London Staff Software Engineer - Machine Learning About this role We're on a mission to transform the way we use data and AI to service our customers and drive efficiency across the business. Do you love shaping the technical landscape and driving innovation across the organisation? Are you passionate about solving complex ML and AI challenges and supporting multiple teams toward a shared technical vision? At Capital One, you'll be part of a community of technical leaders who drive engineering excellence, foster innovation, and deliver impactful ML/AI and Gen AI solutions that meet real customer needs. What You'll Do Own and drive the ML/AI technical strategy for UK use cases, spanning multiple teams and influencing the overall technical direction for AI adoption Lead and coordinate ML engineering efforts across multiple teams, ensuring alignment with broader business objectives, enterprise platform capabilities, and technology strategy Provide technical consultancy to teams delivering AI use cases, guiding architectural decisions, solution design, and effective use of enterprise ML/AI platforms and capabilities Proactively identify emerging ML/AI patterns, define and evangelise best practices, and establish reusable approaches that enhance delivery of AI use cases across the business Drive MLOps standards and practices across teams, including CI/CD for models, automated testing, monitoring, and deployment pipelines Collaborate with enterprise platform and data science teams, contributing to platform capabilities where appropriate and partnering on use case delivery Build and maintain strong relationships with key stakeholders, including senior leadership, product owners, data science teams, and enterprise platform partners Represent Capital One in external ML/AI technical forums, contributing to industry discussions Develop and advocate for strategies to proactively manage technical debt across ML/AI systems Actively mentor and develop engineers, fostering a culture of continuous learning What we're looking for Deep expertise in Python and ML engineering Deep expertise in ML/AI systems design, MLOps, and cloud-native architectures Track record of leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems Experience designing and scaling low-latency, customer-facing ML/AI architectures Proven experience setting a multi-team ML/AI technical vision and strategy Strong track record of technical leadership and influence without authority Experience driving ML engineering standards and best practices across organisations Deep understanding of the full ML/AI development lifecycle, including model serving, data pipelines, and Gen AI systems Experience leveraging enterprise platforms to deliver business use cases at scale Experience of steering Communities of Practice or technical forums Strong business acumen and ability to translate ML/AI concepts for various audiences Where and how you'll work This is a permanent position based in our London office. We have a hybrid working model which gives you flexibility to work from our office and from home. We're big on collaboration and connection, so you'll be based in our London office 3 days a week on Tuesdays, Wednesdays and Thursdays. What's in it for you Bring us all this - and you'll be well rewarded with a role contributing to the roadmap of an organisation committed to transformation We offer high performers strong and diverse career progression, investing heavily in developing great people through our Capital One University training programmes (and appropriate external providers) Immediate access to our core benefits including pension scheme, bonus, generous holiday entitlement and private medical insurance - with flexible benefits available including season-ticket loans, cycle to work scheme and enhanced parental leave Open-plan workspaces and accessible facilities designed to inspire and support you. Our Nottingham head-office has a fully-serviced gym, subsidised restaurant, mindfulness and music rooms. What you should know about how we recruit We pride ourselves on hiring the best people, not the same people. Building diverse and inclusive teams is the right thing to do and the smart thing to do. We want to work with top talent: whoever you are, whatever you look like, wherever you come from. We know it's about what you do, not just what you say. That's why we make our recruitment process fair and accessible. And we offer benefits that attract people at all ages and stages. We also partner with organisations including the Women in Finance and Race At Work Charters, Stonewall and upReach to find people from every walk of life and help them thrive with us. We have a whole host of internal networks and support groups you could be involved in, to name a few: REACH - Race Equality and Culture Heritage group focuses on representation, retention and engagement for associates from minority ethnic groups and allies OutFront - to provide LGBTQ+ support for all associates Mind Your Mind - signposting support and promoting positive mental wellbeing for all Women in Tech - promoting an inclusive environment in tech EmpowHER - network of female associates and allies focusing on developing future leaders, particularly for female talent in our industry Enabled - focused on supporting associates with disabilities and neurodiversity Capital One is committed to diversity in the workplace. If you require a reasonable adjustment, please contact All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). Who We Are At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding. Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.
HypervisionSurgical("Hypervision")is a spin-out from King's College London, founded by clinicians and experts in medical imaging and artificial intelligence. Using safe light alone, our mission is to equip surgeons with real-time, AI-driven tissue intelligence to improve precision and patient safety. We are pioneering the world's first regulatory-cleared real-time intraoperative spectral imaging platform, combining on-chip spectral sensing with high-speed AI analytics at over 60 frames per second. Seamlessly integrating into existing surgical vision systems, our technology transforms standard cameras into intelligent, data-rich tools, revealing anatomical, physiological, and pathological information beyond human vision. Certified for both open and minimally invasive surgery, our platform achievedUKCA certificationandFDA clearancein 2025 under a newly established AI/ML productcode, andwas admitted into the FDA's Safer Technology Program. With multi-centre clinical evaluations underway and strategic partnershipswith world-leading technology and surgical manufactures,includingimecandZEISS Ventures,Hypervisionis shaping the future of data-driven surgery. Hypervision Surgical process all personal data in accordance with the UK GDPR and Data Protection Act 2018. For further information on how we collect, use and protect your data, please refer to our Applicant Privacy Notice. The role We are seeking an experienced Senior Machine Learning Engineer to support the development and deployment of our AI/ML surgical vision platform, taking algorithms from research prototype to production deployment, and building the data pipelines that turn our hyperspectral imaging system into a continuously improving clinical tool. As a Senior Machine Learning Engineer, you will work alongside our research scientists, engineers, and clinical development team to shape both the algorithms and the platform that delivers them. In particular, you will contribute architecturally and in a hands-on capacity to the design, training, evaluation, and production deployment of machine learning models for hyperspectral image processing, including image reconstruction, tissue characterisation, and semantic segmentation design and build the data pipelines that turn raw clinical recordings into structured, governed training datasets, supporting continuous training, model improvement, and re-validation cycles architect and operate the production ML stack, including model versioning, deployment, monitoring, drift detection, and rollback, for our cloud-enabled, regulatory-cleared surgical imaging platform establish and maintain MLOps best practices, including reproducible training, dataset governance, experiment tracking, model documentation, that scale across multiple algorithms, sensors, and clinical indications mentor more junior research scientists and engineers identify and surface novel features in support of patenting activities work closely with our software development and regulatory team for efficient integration from R&D to deployment At Hypervision Surgical, we welcome candidates who have the core skills for the post and are keen to learn and grow with us. We are committed to creating an inclusive environment where a diverse mix of talented people come and enjoy working with each other. By working together, we will change the way surgery is performed and improve patient care. A bitaboutyou PhD or MSc in Machine Learning, Physics, Mathematics, Computer Vision, or related technical discipline 6+ years industry experience designing, training, evaluating, and deploying machine learning models, ideally for vision applications in a regulated medical context Demonstrated track record of taking ML systems from research prototype to production deployment at scale Strong experience building and maintaining data pipelines for continuous training, with a focus on reproducibility, dataset versioning, and efficient access Working knowledge of cloud platforms (AWS, GCP, or Azure) and modern MLOps tooling (e.g. MLflow, Weights & Biases, DVC, Airflow) Strong experience with Python and associated scientific software packages such as PyTorch, OpenCV, Pandas, SciPy, NumPy, SciKit-learn, etc. Strong software engineering practices including version control, code review, software testing methodologies, and continuous integration; experience with IEC 62304 is particularly desirable Excellent oral and written communication skills, and comfort working at the interface between research, engineering, regulatory, and clinical teams Experience mentoring or leading junior engineers or scientists Analytical thinker, attentive to details, creative and team player Bonus points if you bring a special talent, interest, new language, or unique life experience to the team. What we offer The opportunity to make a direct contribution to patient care and deliver real-world surgical impact Access to state-of-the-art surgical development facilities at St Thomas' MedTech Hub, including hospitals, operating rooms, labs, and computational resources, with offices located at the London Institute for Healthcare Engineering Equity participation via share option scheme 25 days of annual leave plus bank holidays Hybrid working arrangements, tailored with your manager to suit the needs of the role Employee Assistance Programme for wellbeing, legal, and financial support Cycle to Work Scheme and Workplace Nursery Benefits £150 annual tech stipend for productivity and office essentials Complimentary office snacks and drinks Monthly team socials in an inclusive, collaborative culture
26/07/2026
Full time
HypervisionSurgical("Hypervision")is a spin-out from King's College London, founded by clinicians and experts in medical imaging and artificial intelligence. Using safe light alone, our mission is to equip surgeons with real-time, AI-driven tissue intelligence to improve precision and patient safety. We are pioneering the world's first regulatory-cleared real-time intraoperative spectral imaging platform, combining on-chip spectral sensing with high-speed AI analytics at over 60 frames per second. Seamlessly integrating into existing surgical vision systems, our technology transforms standard cameras into intelligent, data-rich tools, revealing anatomical, physiological, and pathological information beyond human vision. Certified for both open and minimally invasive surgery, our platform achievedUKCA certificationandFDA clearancein 2025 under a newly established AI/ML productcode, andwas admitted into the FDA's Safer Technology Program. With multi-centre clinical evaluations underway and strategic partnershipswith world-leading technology and surgical manufactures,includingimecandZEISS Ventures,Hypervisionis shaping the future of data-driven surgery. Hypervision Surgical process all personal data in accordance with the UK GDPR and Data Protection Act 2018. For further information on how we collect, use and protect your data, please refer to our Applicant Privacy Notice. The role We are seeking an experienced Senior Machine Learning Engineer to support the development and deployment of our AI/ML surgical vision platform, taking algorithms from research prototype to production deployment, and building the data pipelines that turn our hyperspectral imaging system into a continuously improving clinical tool. As a Senior Machine Learning Engineer, you will work alongside our research scientists, engineers, and clinical development team to shape both the algorithms and the platform that delivers them. In particular, you will contribute architecturally and in a hands-on capacity to the design, training, evaluation, and production deployment of machine learning models for hyperspectral image processing, including image reconstruction, tissue characterisation, and semantic segmentation design and build the data pipelines that turn raw clinical recordings into structured, governed training datasets, supporting continuous training, model improvement, and re-validation cycles architect and operate the production ML stack, including model versioning, deployment, monitoring, drift detection, and rollback, for our cloud-enabled, regulatory-cleared surgical imaging platform establish and maintain MLOps best practices, including reproducible training, dataset governance, experiment tracking, model documentation, that scale across multiple algorithms, sensors, and clinical indications mentor more junior research scientists and engineers identify and surface novel features in support of patenting activities work closely with our software development and regulatory team for efficient integration from R&D to deployment At Hypervision Surgical, we welcome candidates who have the core skills for the post and are keen to learn and grow with us. We are committed to creating an inclusive environment where a diverse mix of talented people come and enjoy working with each other. By working together, we will change the way surgery is performed and improve patient care. A bitaboutyou PhD or MSc in Machine Learning, Physics, Mathematics, Computer Vision, or related technical discipline 6+ years industry experience designing, training, evaluating, and deploying machine learning models, ideally for vision applications in a regulated medical context Demonstrated track record of taking ML systems from research prototype to production deployment at scale Strong experience building and maintaining data pipelines for continuous training, with a focus on reproducibility, dataset versioning, and efficient access Working knowledge of cloud platforms (AWS, GCP, or Azure) and modern MLOps tooling (e.g. MLflow, Weights & Biases, DVC, Airflow) Strong experience with Python and associated scientific software packages such as PyTorch, OpenCV, Pandas, SciPy, NumPy, SciKit-learn, etc. Strong software engineering practices including version control, code review, software testing methodologies, and continuous integration; experience with IEC 62304 is particularly desirable Excellent oral and written communication skills, and comfort working at the interface between research, engineering, regulatory, and clinical teams Experience mentoring or leading junior engineers or scientists Analytical thinker, attentive to details, creative and team player Bonus points if you bring a special talent, interest, new language, or unique life experience to the team. What we offer The opportunity to make a direct contribution to patient care and deliver real-world surgical impact Access to state-of-the-art surgical development facilities at St Thomas' MedTech Hub, including hospitals, operating rooms, labs, and computational resources, with offices located at the London Institute for Healthcare Engineering Equity participation via share option scheme 25 days of annual leave plus bank holidays Hybrid working arrangements, tailored with your manager to suit the needs of the role Employee Assistance Programme for wellbeing, legal, and financial support Cycle to Work Scheme and Workplace Nursery Benefits £150 annual tech stipend for productivity and office essentials Complimentary office snacks and drinks Monthly team socials in an inclusive, collaborative culture
Birmingham, United Kingdom / Brighton, United Kingdom / Bristol, United Kingdom / Cardiff, United Kingdom / Glasgow, United Kingdom / London, United Kingdom / Manchester, United Kingdom / Newcastle Upon Tyne, United Kingdom Location/s: London, Cardiff, Bristol, Brighton, Birmingham, Manchester, Glasgow, Newcastle Relocation supported:Not supported, but internal applications are welcome Hiring manager contact: Sam Ahdab Mott MacDonald is a global engineering, management, and development consultancy with over 20,000 employees across more than 50 countries and 140+ offices. We work across incredible global industries, delivering exciting work that is defining our future and making an important societal impact in the communities we serve. Our people power our performance - we succeed when they do. With countless opportunities to collaborate, learn, and grow, the possibilities for excellence are as varied as every individual. Whether you want to grow as a subject matter expert or broaden your experience with roles across our international community, you're surrounded by global specialists who want to combine their expertise and champion you to be your best. As a proudly employee owned business, we benefit our clients, our communities, and each other, investing in creating the right space for everyone to feel empowered, included, and valued. Whatever your ambition, Mott MacDonald is where people come to be brilliant. Overview of the role: We are looking for a Principal Data Scientist to help shape the design, development and delivery of production grade AI, machine learning and data science solutions across Mott MacDonald. The role will focus on turning complex business, engineering and environmental needs into scalable, reliable data products and AI services. The successful candidate will bring technical experience across generative AI, large language models, retrieval augmented generation, machine learning, computer vision, geospatial data science and MLOps. They will work with multidisciplinary teams to identify valuable use cases, shape solution architecture, develop reliable models and ensure solutions are tested, monitored and improved in live use. The role includes end to end AI and data science delivery; setting standards for model development, evaluation and deployment; building reusable internal AI services; coaching data scientists and engineers; contributing to AI governance; and translating technical opportunities into clear business value for project teams and senior stakeholders. Candidate Specifications: Experience delivering production data science, machine learning or AI in an enterprise environment. Practical experience in Python and modern machine learning frameworks such as PyTorch, TensorFlow or Keras. Practical experience with generative AI, large language models, embedding models, retrieval augmented generation, AI agents, model evaluation and fine tuning techniques. Experience designing and operating end to end MLOps workflows, including model training, deployment, monitoring, automation and continuous improvement. Ability to work across cloud and engineering environments, including tools such as Azure, Kubernetes, Docker, MLflow, GitHub Actions, Terraform or Databricks. Clear communication and stakeholder engagement skills, with the ability to explain complex technical concepts in accessible business language. Experience coaching, mentoring or giving technical guidance to data scientists, machine learning engineers or data professionals Experience applying computer vision, geospatial data science or predictive modelling to engineering, infrastructure, environmental or asset management work. Knowledge of tools and methods such as LangChain, LLM orchestration, agentic tool use, segmentation foundation models, zero/few shot visual understanding Experience developing reusable internal AI platforms, foundation model services or automation capabilities for use by wider teams. Postgraduate qualification or equivalent research experience in data science, engineering, computer science, applied mathematics or a related discipline. Evidence of innovation, publication, award recognition or contribution to data science practice. UK Immigration Mott MacDonald Ltd. are not currently offering sponsorship to candidates under the Skilled Worker visa route in the UK. This decision is as a consequence of the changes made to the Skilled Worker route by the UK Government in April 2024. We continue to welcome applications from candidates who are eligible for alternative immigration routes in the UK, that do not require sponsorship as a Skilled Worker now or in future. At Mott MacDonald, we believe it makes business sense for you and your manager to choose how you can work most effectively to meet your client, team, and personal commitments. We offer a hybrid working policy that embraces your well being, flexibility, and trust. Equality, diversity, and inclusion We put equality, diversity, and inclusion at the heart of our business, seeking to promote fair employment procedures and practices to ensure equal opportunities for all. We encourage individual expression in our workplace and are committed to creating an inclusive environment where everyone feels they can contribute. Accessibility We want you to perform your best at every stage in the recruitment process. If you are disabled or need any support to enable you to apply or attend an interview, please contact us at and we will talk to you about how we can support you. Financial wellbeing We match employee pension contributions between 4.5% and 7%. Life assurance equal up to 4 x your basic salary, with an option to increase the level of cover to 6 x your salary. Our income protection scheme provides a financial benefit, as well as absence and return to work support due to long term illness or injury. Flexible benefits, including increased life assurance cover, critical illness insurance, payroll saving and will writing. As an independently owned business we share the financial success of the business with all our colleagues in various ways including annual bonus schemes. Employee Ownership Our employee ownership model means no external investors, just us, creating a culture of shared success. Our employees have a stake and a voice in our business, giving them a direct connection to our success through our personal and group performance bonuses. As your career grows, so does your stake, recognising your long term impact and contribution. Your voice matters, with the opportunity to connect directly with senior leadership through formal channels to help shape our future. For our senior roles you will have a direct pathway towards ownership from day one. Health and wellbeing Private medical insurance for all UK colleagues. Health cash plan to support you with every day health costs and treatments. Access to Peppy, providing free support from menopause experts for all UK colleagues. A variety of wellbeing support is available through our comprehensive wellbeing program, including access for you and your family. Ability to flex your salary to opt into a wide range of health benefits, many of which can be extended to your family too. Lifestyle A minimum of 33-35 days holiday each year, inclusive of public holidays and dependent on level, with the ability to buy or sell leave through our flexible benefits programme. 10 days additional paid leave for Armed Forces Reservists and Cadet Force Adult Volunteers. Holiday entitlement increased to a minimum of 35 days after 5 years' service. Variety of employee saving schemes and discounts from high street retailers. Enhanced family and carers leave Enhanced family leave policies, including 26 weeks paid maternity and adoption leave, and two weeks paid paternity/partner leave. Our shared parental leave matches maternity leave meaning we pay up to 24 weeks at full pay. Up to five additional days leave are provided for those with significant caring responsibilities, two of which are paid. We offer policies and dedicated support to help military families balance service life with career and wellbeing. Learning and development Primary annual professional institution subscription. A broad range of opportunities to enhance both technical and soft skills through mentoring, formal training, and self development options. Networks, communities, and social outcomes Join a wide range of groups including our Advanced Employee Networks which support our LGBTQ+, gender, race and ethnicity, disability, and parents/carers communities. We are proud signatories of the Armed Forces Covenant and Gold Award holders in the MOD Employer Recognition Scheme, supported by our dedicated internal Armed Forces Network.
26/07/2026
Full time
Birmingham, United Kingdom / Brighton, United Kingdom / Bristol, United Kingdom / Cardiff, United Kingdom / Glasgow, United Kingdom / London, United Kingdom / Manchester, United Kingdom / Newcastle Upon Tyne, United Kingdom Location/s: London, Cardiff, Bristol, Brighton, Birmingham, Manchester, Glasgow, Newcastle Relocation supported:Not supported, but internal applications are welcome Hiring manager contact: Sam Ahdab Mott MacDonald is a global engineering, management, and development consultancy with over 20,000 employees across more than 50 countries and 140+ offices. We work across incredible global industries, delivering exciting work that is defining our future and making an important societal impact in the communities we serve. Our people power our performance - we succeed when they do. With countless opportunities to collaborate, learn, and grow, the possibilities for excellence are as varied as every individual. Whether you want to grow as a subject matter expert or broaden your experience with roles across our international community, you're surrounded by global specialists who want to combine their expertise and champion you to be your best. As a proudly employee owned business, we benefit our clients, our communities, and each other, investing in creating the right space for everyone to feel empowered, included, and valued. Whatever your ambition, Mott MacDonald is where people come to be brilliant. Overview of the role: We are looking for a Principal Data Scientist to help shape the design, development and delivery of production grade AI, machine learning and data science solutions across Mott MacDonald. The role will focus on turning complex business, engineering and environmental needs into scalable, reliable data products and AI services. The successful candidate will bring technical experience across generative AI, large language models, retrieval augmented generation, machine learning, computer vision, geospatial data science and MLOps. They will work with multidisciplinary teams to identify valuable use cases, shape solution architecture, develop reliable models and ensure solutions are tested, monitored and improved in live use. The role includes end to end AI and data science delivery; setting standards for model development, evaluation and deployment; building reusable internal AI services; coaching data scientists and engineers; contributing to AI governance; and translating technical opportunities into clear business value for project teams and senior stakeholders. Candidate Specifications: Experience delivering production data science, machine learning or AI in an enterprise environment. Practical experience in Python and modern machine learning frameworks such as PyTorch, TensorFlow or Keras. Practical experience with generative AI, large language models, embedding models, retrieval augmented generation, AI agents, model evaluation and fine tuning techniques. Experience designing and operating end to end MLOps workflows, including model training, deployment, monitoring, automation and continuous improvement. Ability to work across cloud and engineering environments, including tools such as Azure, Kubernetes, Docker, MLflow, GitHub Actions, Terraform or Databricks. Clear communication and stakeholder engagement skills, with the ability to explain complex technical concepts in accessible business language. Experience coaching, mentoring or giving technical guidance to data scientists, machine learning engineers or data professionals Experience applying computer vision, geospatial data science or predictive modelling to engineering, infrastructure, environmental or asset management work. Knowledge of tools and methods such as LangChain, LLM orchestration, agentic tool use, segmentation foundation models, zero/few shot visual understanding Experience developing reusable internal AI platforms, foundation model services or automation capabilities for use by wider teams. Postgraduate qualification or equivalent research experience in data science, engineering, computer science, applied mathematics or a related discipline. Evidence of innovation, publication, award recognition or contribution to data science practice. UK Immigration Mott MacDonald Ltd. are not currently offering sponsorship to candidates under the Skilled Worker visa route in the UK. This decision is as a consequence of the changes made to the Skilled Worker route by the UK Government in April 2024. We continue to welcome applications from candidates who are eligible for alternative immigration routes in the UK, that do not require sponsorship as a Skilled Worker now or in future. At Mott MacDonald, we believe it makes business sense for you and your manager to choose how you can work most effectively to meet your client, team, and personal commitments. We offer a hybrid working policy that embraces your well being, flexibility, and trust. Equality, diversity, and inclusion We put equality, diversity, and inclusion at the heart of our business, seeking to promote fair employment procedures and practices to ensure equal opportunities for all. We encourage individual expression in our workplace and are committed to creating an inclusive environment where everyone feels they can contribute. Accessibility We want you to perform your best at every stage in the recruitment process. If you are disabled or need any support to enable you to apply or attend an interview, please contact us at and we will talk to you about how we can support you. Financial wellbeing We match employee pension contributions between 4.5% and 7%. Life assurance equal up to 4 x your basic salary, with an option to increase the level of cover to 6 x your salary. Our income protection scheme provides a financial benefit, as well as absence and return to work support due to long term illness or injury. Flexible benefits, including increased life assurance cover, critical illness insurance, payroll saving and will writing. As an independently owned business we share the financial success of the business with all our colleagues in various ways including annual bonus schemes. Employee Ownership Our employee ownership model means no external investors, just us, creating a culture of shared success. Our employees have a stake and a voice in our business, giving them a direct connection to our success through our personal and group performance bonuses. As your career grows, so does your stake, recognising your long term impact and contribution. Your voice matters, with the opportunity to connect directly with senior leadership through formal channels to help shape our future. For our senior roles you will have a direct pathway towards ownership from day one. Health and wellbeing Private medical insurance for all UK colleagues. Health cash plan to support you with every day health costs and treatments. Access to Peppy, providing free support from menopause experts for all UK colleagues. A variety of wellbeing support is available through our comprehensive wellbeing program, including access for you and your family. Ability to flex your salary to opt into a wide range of health benefits, many of which can be extended to your family too. Lifestyle A minimum of 33-35 days holiday each year, inclusive of public holidays and dependent on level, with the ability to buy or sell leave through our flexible benefits programme. 10 days additional paid leave for Armed Forces Reservists and Cadet Force Adult Volunteers. Holiday entitlement increased to a minimum of 35 days after 5 years' service. Variety of employee saving schemes and discounts from high street retailers. Enhanced family and carers leave Enhanced family leave policies, including 26 weeks paid maternity and adoption leave, and two weeks paid paternity/partner leave. Our shared parental leave matches maternity leave meaning we pay up to 24 weeks at full pay. Up to five additional days leave are provided for those with significant caring responsibilities, two of which are paid. We offer policies and dedicated support to help military families balance service life with career and wellbeing. Learning and development Primary annual professional institution subscription. A broad range of opportunities to enhance both technical and soft skills through mentoring, formal training, and self development options. Networks, communities, and social outcomes Join a wide range of groups including our Advanced Employee Networks which support our LGBTQ+, gender, race and ethnicity, disability, and parents/carers communities. We are proud signatories of the Armed Forces Covenant and Gold Award holders in the MOD Employer Recognition Scheme, supported by our dedicated internal Armed Forces Network.
At Bionic, we're on a mission to make it radically easier to run a small business. As the UK's leading business comparison and switching service, we help thousands of small and medium size businesses save time and money on essentials like energy, broadband, insurance, and finance. We combine smart technology with real human support to match our customers with the best deals - quickly and effortlessly. With trusted partnerships including Compare the Market, Uswitch for Business, MoneySuperMarket and we're committed to help SMEs get the best deals for their business essentials every time. Role As a Senior Data Engineer you'll be responsible for designing, building, and scaling robust, high quality data platforms that underpin critical business reporting and operational decision making. You will drive the development of data pipelines, models, and architecture across our modern data stack (AWS, Snowflake, dbt) ensuring performance, reliability, and scalability. Working closely with Architecture, Data Analytics, and Salesforce teams, you will drive the evolution of our data platform, guide best practices, and play a key role in modernising legacy processes. You will act as a technical leader within the team, shaping design decisions, mentoring engineers, and ensuring delivery of resilient, well governed data products. This role requires strong technical expertise, strategic thinking, and the ability to translate complex business needs into scalable, production grade data solutions. Key Responsibilities Design, build and optimise scalable data pipelines and data products across AWS, Snowflake and dbt, setting engineering standards and best practices. Lead the development of robust, testable dbt models and frameworks to ensure high data quality, consistency, and maintainability. Own data pipeline reliability, proactively monitoring, troubleshooting, and resolving complex data and performance issues with minimal disruption. Architect and evolve analytics ready data models (e.g., star schemas, data marts), balancing performance, flexibility, and usability. Collaborate with senior stakeholders (Analytics, Salesforce, Architecture) to define requirements and translate them into scalable technical solutions. Drive continuous improvement of data engineering practices, including CI/CD, observability, testing frameworks, and documentation standards. Provide technical leadership through mentoring, code reviews, and guidance to junior team members, fostering engineering excellence. Ensure compliance with security, governance, and data privacy requirements, embedding best practices in all solutions. Contribute to strategic data platform decisions, including tooling, architecture, and long term roadmap planning. Essential Skills and Experience Required Proven experience designing, building and maintaining scalable data pipelines and cloud based data platforms in production environments. Advanced SQL expertise, including query optimisation, performance tuning and complex data transformations. Strong Python skills for data engineering, automation and system integrations. Hands on experience with Snowflake (or similar cloud data warehouse), including data modelling, optimisation and security/access controls. Strong experience with dbt, including modelling, testing and deployment best practices. Solid knowledge of AWS data services and cloud native architectures (e.g. S3, Lambda, IAM, CloudWatch). Experience with modern software engineering practices, including Git, CI/CD and automated testing. Strong understanding of data modelling and data warehousing principles. Ability to solve complex problems, identify root causes and deliver scalable, reliable solutions. Experience leading technical delivery, influencing architectural decisions and collaborating across multiple stakeholders. Comfortable working in ambiguity, translating complex business requirements into structured technical solutions. Strong communication skills, with the ability to engage both technical and non technical audiences. Nice to have Experience with real time or streaming data architectures. Exposure to Salesforce data models and API integrations. Experience using AWS CDK for infrastructure deployment. Familiarity with orchestration tools such as Airflow. Experience implementing data observability, monitoring and alerting solutions. Knowledge of BI platforms such as Tableau and how data products are consumed by end users. Exposure to MLOps practices, including supporting machine learning pipelines, model deployment and monitoring. Awareness of emerging trends, technologies and best practices within modern data engineering. Why Join Bionic At Bionic, better never stops. You'll join a team obsessed with improvement, innovation and impact - where your expertise will directly shape how thousands of British businesses grow and thrive. Benefits We know that our employees are what sets us aside from our competitors; our benefits are just part of the way we say thanks. Health & Wellbeing Private healthcare cover Employee Assistance Programme, including a virtual GP service, priority physio & talking therapies Eyecare scheme Time Off 25 days annual leave plus the 8 UK bank holidays, increasing with tenure 1 paid family/religious day of leave per year - following successful probation period 1 paid charity volunteering day per year Option to buy/sell up to an additional 3 days leave per year Family Matters Enhanced maternity, paternity or shared parental leave 2 days off for your wedding upon joining, and up to 5 days after 2 years service Flexible working options & a hybrid work approach Financial Wellbeing Auto enrolled salary sacrifice pension scheme Life assurance Season ticket loans, salary advances & loans to buy or rent a home - based on tenure Cycle to work scheme Recognition Highflyers incentive, a VIP experience for our high performers across Bionic group to celebrate success Company summer & Christmas party celebrations, business and local zone & annual awards and recognition Long service awards
25/07/2026
Full time
At Bionic, we're on a mission to make it radically easier to run a small business. As the UK's leading business comparison and switching service, we help thousands of small and medium size businesses save time and money on essentials like energy, broadband, insurance, and finance. We combine smart technology with real human support to match our customers with the best deals - quickly and effortlessly. With trusted partnerships including Compare the Market, Uswitch for Business, MoneySuperMarket and we're committed to help SMEs get the best deals for their business essentials every time. Role As a Senior Data Engineer you'll be responsible for designing, building, and scaling robust, high quality data platforms that underpin critical business reporting and operational decision making. You will drive the development of data pipelines, models, and architecture across our modern data stack (AWS, Snowflake, dbt) ensuring performance, reliability, and scalability. Working closely with Architecture, Data Analytics, and Salesforce teams, you will drive the evolution of our data platform, guide best practices, and play a key role in modernising legacy processes. You will act as a technical leader within the team, shaping design decisions, mentoring engineers, and ensuring delivery of resilient, well governed data products. This role requires strong technical expertise, strategic thinking, and the ability to translate complex business needs into scalable, production grade data solutions. Key Responsibilities Design, build and optimise scalable data pipelines and data products across AWS, Snowflake and dbt, setting engineering standards and best practices. Lead the development of robust, testable dbt models and frameworks to ensure high data quality, consistency, and maintainability. Own data pipeline reliability, proactively monitoring, troubleshooting, and resolving complex data and performance issues with minimal disruption. Architect and evolve analytics ready data models (e.g., star schemas, data marts), balancing performance, flexibility, and usability. Collaborate with senior stakeholders (Analytics, Salesforce, Architecture) to define requirements and translate them into scalable technical solutions. Drive continuous improvement of data engineering practices, including CI/CD, observability, testing frameworks, and documentation standards. Provide technical leadership through mentoring, code reviews, and guidance to junior team members, fostering engineering excellence. Ensure compliance with security, governance, and data privacy requirements, embedding best practices in all solutions. Contribute to strategic data platform decisions, including tooling, architecture, and long term roadmap planning. Essential Skills and Experience Required Proven experience designing, building and maintaining scalable data pipelines and cloud based data platforms in production environments. Advanced SQL expertise, including query optimisation, performance tuning and complex data transformations. Strong Python skills for data engineering, automation and system integrations. Hands on experience with Snowflake (or similar cloud data warehouse), including data modelling, optimisation and security/access controls. Strong experience with dbt, including modelling, testing and deployment best practices. Solid knowledge of AWS data services and cloud native architectures (e.g. S3, Lambda, IAM, CloudWatch). Experience with modern software engineering practices, including Git, CI/CD and automated testing. Strong understanding of data modelling and data warehousing principles. Ability to solve complex problems, identify root causes and deliver scalable, reliable solutions. Experience leading technical delivery, influencing architectural decisions and collaborating across multiple stakeholders. Comfortable working in ambiguity, translating complex business requirements into structured technical solutions. Strong communication skills, with the ability to engage both technical and non technical audiences. Nice to have Experience with real time or streaming data architectures. Exposure to Salesforce data models and API integrations. Experience using AWS CDK for infrastructure deployment. Familiarity with orchestration tools such as Airflow. Experience implementing data observability, monitoring and alerting solutions. Knowledge of BI platforms such as Tableau and how data products are consumed by end users. Exposure to MLOps practices, including supporting machine learning pipelines, model deployment and monitoring. Awareness of emerging trends, technologies and best practices within modern data engineering. Why Join Bionic At Bionic, better never stops. You'll join a team obsessed with improvement, innovation and impact - where your expertise will directly shape how thousands of British businesses grow and thrive. Benefits We know that our employees are what sets us aside from our competitors; our benefits are just part of the way we say thanks. Health & Wellbeing Private healthcare cover Employee Assistance Programme, including a virtual GP service, priority physio & talking therapies Eyecare scheme Time Off 25 days annual leave plus the 8 UK bank holidays, increasing with tenure 1 paid family/religious day of leave per year - following successful probation period 1 paid charity volunteering day per year Option to buy/sell up to an additional 3 days leave per year Family Matters Enhanced maternity, paternity or shared parental leave 2 days off for your wedding upon joining, and up to 5 days after 2 years service Flexible working options & a hybrid work approach Financial Wellbeing Auto enrolled salary sacrifice pension scheme Life assurance Season ticket loans, salary advances & loans to buy or rent a home - based on tenure Cycle to work scheme Recognition Highflyers incentive, a VIP experience for our high performers across Bionic group to celebrate success Company summer & Christmas party celebrations, business and local zone & annual awards and recognition Long service awards
Funding Circle is building a central AI and Machine Learning platform in London, combining a data-driven approach with scalable cloud infrastructure. This senior, hands-on role focuses on developing, deploying, and managing AI applications and agents across the business. Join a high-impact team that designs end-to-end AI tooling, collaborates with product and security teams, and embraces a flexible, hybrid work model in a fintech environment.
25/07/2026
Full time
Funding Circle is building a central AI and Machine Learning platform in London, combining a data-driven approach with scalable cloud infrastructure. This senior, hands-on role focuses on developing, deploying, and managing AI applications and agents across the business. Join a high-impact team that designs end-to-end AI tooling, collaborates with product and security teams, and embraces a flexible, hybrid work model in a fintech environment.
Job Details Salary: Competitive Plus Benefits Location: London Store Support Centre, London, EC1M 6HA Contract type: Permanent Business area: Sainsbury's Tech Closing date: 29 July 2026 Requisition ID: Job Title Senior Machine Learning Engineer Job Overview As a Senior Machine Learning Engineer, you will play a pivotal role in designing, building, and optimising a Machine Learning system for Advert Classification. We are looking for a leader competent across modern ML tooling, methodologies, and design practices, while also able to design hybrid systems that integrate LLMs. The lead is expected to drive the ML design and build lifecycle, arriving at a reliable and performant system, supporting a team of Data Scientists in delivery. Systematic evaluation of performance with data is a critical part of our ML initiatives; the lead will drive strategy and operationalise automatic machine evaluation with metrics and best practice MLOps. You will partner with Data Scientists and Software Engineers to ensure the system is reliable, performant, and production ready. You will also contribute to engineering excellence across Machine Learning and MLOps by driving best practices, mentoring other engineers, and shaping the technical direction of data and ML workflows across our domain. Key Responsibilities Lead the design and build of high quality, scalable, and reusable Machine Learning systems using Sainsbury's engineering standards and best practices. Design and optimise Machine Learning modules for Advert classification, applying the ML Lifecycle and best practice in model selection and development. Lead the design and implementation of supporting Machine Learning Operations, applying best in class approaches to data versioning, model re training, and data observability. Implement automation tools and frameworks for experiment tracking, data and model observability to streamline deployment and monitoring of machine learning models in production. Lead the system evaluation methodology, including evaluation strategy, data generation, and evaluation metrics. Provide guidance to mid level Data Scientists on best practice and methodological choices when optimising machine learning modules and the system overall; offer technical guidance on emerging technologies in data engineering and machine learning to enhance their skills and career growth. Collaborate and support with data scientists across the lifecycle, including EDA, data transformation, model selection, feature engineering, and model selection. Optimise data processing workflows and storage solutions to improve performance and reduce costs. Work closely with cross functional teams, including software engineering and product management, to deliver data solutions that meet business needs. Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews. Encourage continuous learning and improvement, fostering a collaborative and inclusive team environment. Have 6-10 years of experience designing and building Machine Learning systems end to end, including strong experience implementing MLOps. Qualifications Strong understanding of modern Machine Learning methodologies, Data Science, and accompanying algorithms. Good experience integrating LLMs as hybrid AI ML systems. Academic background with at least a BSc in Computer Science. Experience in modern Computer Vision, having built image detection systems end to end. Strong understanding of ML deployment and management on modern Cloud platforms, specifically MS Azure and AWS. Strong analytical and problem solving skills. Excellent communication skills, able to explain complex concepts to non technical stakeholders. Ability to work independently as well as collaboratively within cross functional teams. Leadership and Communication Provide technical direction, set standards, and lead by example in science and engineering excellence. Facilitate Scrum ceremonies when required (stand ups, planning, grooming). Communicate clearly and transparently, creating an inclusive environment where diverse opinions are encouraged. Strong team player with a collaborative approach to working with cross functional teams within the Media Agency. Open to feedback and willing to provide constructive criticism to others. Be available for the team, responding within a reasonable time frame, and if not possible, clearly signpost alternative contacts who can guide. Build a community across the Media Agency. Contribute to a positive and inclusive atmosphere within the team. Knowledge Sharing and Empowerment Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels. Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap. Deliver Through Others Share domain expertise proactively and help establish the engineering direction for the team. Support spikes, POCs and early investigative work. Lead by example in communication, visibility, accountability and role modeling Sainsbury's values. Benefits Starting off with colleague discount, you will be able to get 10% off at Sainsbury's, Argos, TU and Habitat after 4 weeks. This increases to 15% off at Sainsbury's every Friday and Saturday and 15% off at Argos every pay day. We also have pensions scheme and life cover, and you may be eligible for a performance related bonus of up to 20% of salary, depending on how we perform. Your wellbeing is important to us too. You will receive an annual holiday allowance, and you can buy additional holiday. We also offer other benefits that will help your money go further such as season ticket loans, interest free car loan of up to £10k, cycle to work scheme, health cash plans, pay advance, and access to a great range of discounts from hundreds of other retailers. There is also an Employee Assistance Programme, and you will be eligible for private healthcare. We provide up to 26 weeks' pay for maternity or adoption leave and up to 4 weeks' pay for paternity leave.
25/07/2026
Full time
Job Details Salary: Competitive Plus Benefits Location: London Store Support Centre, London, EC1M 6HA Contract type: Permanent Business area: Sainsbury's Tech Closing date: 29 July 2026 Requisition ID: Job Title Senior Machine Learning Engineer Job Overview As a Senior Machine Learning Engineer, you will play a pivotal role in designing, building, and optimising a Machine Learning system for Advert Classification. We are looking for a leader competent across modern ML tooling, methodologies, and design practices, while also able to design hybrid systems that integrate LLMs. The lead is expected to drive the ML design and build lifecycle, arriving at a reliable and performant system, supporting a team of Data Scientists in delivery. Systematic evaluation of performance with data is a critical part of our ML initiatives; the lead will drive strategy and operationalise automatic machine evaluation with metrics and best practice MLOps. You will partner with Data Scientists and Software Engineers to ensure the system is reliable, performant, and production ready. You will also contribute to engineering excellence across Machine Learning and MLOps by driving best practices, mentoring other engineers, and shaping the technical direction of data and ML workflows across our domain. Key Responsibilities Lead the design and build of high quality, scalable, and reusable Machine Learning systems using Sainsbury's engineering standards and best practices. Design and optimise Machine Learning modules for Advert classification, applying the ML Lifecycle and best practice in model selection and development. Lead the design and implementation of supporting Machine Learning Operations, applying best in class approaches to data versioning, model re training, and data observability. Implement automation tools and frameworks for experiment tracking, data and model observability to streamline deployment and monitoring of machine learning models in production. Lead the system evaluation methodology, including evaluation strategy, data generation, and evaluation metrics. Provide guidance to mid level Data Scientists on best practice and methodological choices when optimising machine learning modules and the system overall; offer technical guidance on emerging technologies in data engineering and machine learning to enhance their skills and career growth. Collaborate and support with data scientists across the lifecycle, including EDA, data transformation, model selection, feature engineering, and model selection. Optimise data processing workflows and storage solutions to improve performance and reduce costs. Work closely with cross functional teams, including software engineering and product management, to deliver data solutions that meet business needs. Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews. Encourage continuous learning and improvement, fostering a collaborative and inclusive team environment. Have 6-10 years of experience designing and building Machine Learning systems end to end, including strong experience implementing MLOps. Qualifications Strong understanding of modern Machine Learning methodologies, Data Science, and accompanying algorithms. Good experience integrating LLMs as hybrid AI ML systems. Academic background with at least a BSc in Computer Science. Experience in modern Computer Vision, having built image detection systems end to end. Strong understanding of ML deployment and management on modern Cloud platforms, specifically MS Azure and AWS. Strong analytical and problem solving skills. Excellent communication skills, able to explain complex concepts to non technical stakeholders. Ability to work independently as well as collaboratively within cross functional teams. Leadership and Communication Provide technical direction, set standards, and lead by example in science and engineering excellence. Facilitate Scrum ceremonies when required (stand ups, planning, grooming). Communicate clearly and transparently, creating an inclusive environment where diverse opinions are encouraged. Strong team player with a collaborative approach to working with cross functional teams within the Media Agency. Open to feedback and willing to provide constructive criticism to others. Be available for the team, responding within a reasonable time frame, and if not possible, clearly signpost alternative contacts who can guide. Build a community across the Media Agency. Contribute to a positive and inclusive atmosphere within the team. Knowledge Sharing and Empowerment Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels. Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap. Deliver Through Others Share domain expertise proactively and help establish the engineering direction for the team. Support spikes, POCs and early investigative work. Lead by example in communication, visibility, accountability and role modeling Sainsbury's values. Benefits Starting off with colleague discount, you will be able to get 10% off at Sainsbury's, Argos, TU and Habitat after 4 weeks. This increases to 15% off at Sainsbury's every Friday and Saturday and 15% off at Argos every pay day. We also have pensions scheme and life cover, and you may be eligible for a performance related bonus of up to 20% of salary, depending on how we perform. Your wellbeing is important to us too. You will receive an annual holiday allowance, and you can buy additional holiday. We also offer other benefits that will help your money go further such as season ticket loans, interest free car loan of up to £10k, cycle to work scheme, health cash plans, pay advance, and access to a great range of discounts from hundreds of other retailers. There is also an Employee Assistance Programme, and you will be eligible for private healthcare. We provide up to 26 weeks' pay for maternity or adoption leave and up to 4 weeks' pay for paternity leave.
OUR MISSION To become the car-changing destination of choice. By combining technology, media and deep automotive expertise, we've turned how people buy, sell, advertise and lease cars on its head. What started as a simple reviews site is now one of the largest online car-changing destinations in Europe. Last year alone we grew over 50% with nearly £3bn worth of cars bought on site, while £1.8bn of cars were listed for sale through our Sell My Car service. In 2024 we went big and acquired Autovia - creators of AutoExpress and Evo magazines - doubling our audience overnight. Together we now have one of the biggest YouTube channels in the world with almost 10m subscribers and over 1.1 billion annual views, while we sell 1.2 million print copies of our magazines and have an annual web content reach over 350million. And we're a long way from done! THE ROLE We're looking for a Senior Data Scientist to join our award-winning Data Science team at a pivotal moment. Carwow operates a two-sided marketplace - connecting car buyers and sellers at scale - and data science sits at the heart of how we make that marketplace smarter, faster, and more valuable for everyone in it. In fact, we recently won GenAI initiative of the Year at the British Data Awards. This is a hands on, high ownership role working centrally across the business. You'll partner with teams spanning Commercial, Marketing, Product, Finance, Engineering and Operations - developing and deploying ML and AI solutions that drive outcomes across both sides of our marketplace. The problems you'll work on are genuinely varied: pricing models, propensity and demand signals that sharpen marketing spend, personalised recommendations for our web product and CRM, and LLM powered solutions for operational challenges like document verification. You'll translate ambiguous business problems into structured, production ready solutions - and you'll be expected to deliver them end to end, from first principles through to being deployment ready and beyond. WHAT YOU'LL BE DOING End-to-End ML & AI Delivery: Lead data science initiatives from problem framing through to deployment, monitoring, and iteration - delivering the full production lifecycle. With no dedicated ML engineering function, you'll be responsible for ensuring your solutions are robust, scalable, and performing in the real world long after they ship. GenAI & LLM Application: Design and build LLM-powered solutions where they create genuine business value - document processing, intelligent search, content understanding, and beyond. Apply them alongside classical ML with clear judgement about where each approach earns its place. Commercial Impact: Connect your work directly to business outcomes. Whether you're building a model to improve marketing efficiency, a pricing signal to sharpen commercial decisions, or a recommendation engine to increase conversion - you understand the business lever you're pulling and design your solutions accordingly. Prototyping & Experimentation: Move fast to test ideas before committing to full scale development. Define rigorous success metrics upfront, validate honestly, and know when to double down and when to walk away. Cross Functional Partnership: Work closely with Commercial, Marketing, Product, Finance, Engineering and Operations stakeholders to understand problems deeply before reaching for a solution. Translate findings into clear, actionable narratives for both technical and non-technical audiences. Standards & Craft: Contribute to shared best practices, documentation, and ways of working that raise the bar for the data science function - and help more junior team members grow alongside you. Drive continued adoption of AI capabilities to drive efficiencies, automation and constantly leverage new capabilities. WHAT YOU'LL NEED Please note: We know that no candidate will be the perfect match for all we've listed in this posting, so we'd encourage you to apply if you feel you're close to the brief but not an exact match. Ideally you'll have Commercial Mindset: You think about business impact first. You understand how your models connect to revenue, efficiency, or customer outcomes - and you use that to prioritise, scope, and communicate your work. Stakeholder Partnership: Proven ability to work with commercial, marketing, and product stakeholders - translating business problems into well scoped solutions and communicating technical solutions, challenges and outcomes clearly at all levels. Sound Judgement: You navigate the tooling landscape with clear eyes - knowing when classical ML is right, when GenAI unlocks something new, and when a simpler solution is the more honest answer. Strong instincts for scalability, reliability, and explainability. Bonus Marketplace or Two Sided Platform Experience: Understanding of supply/demand dynamics and how data science creates leverage in a marketplace context. TEHCNICAL SKILLSET Proven ML Experience: A strong track record of building, deploying, and maintaining ML models in Python in a production environment - not just notebooks. You've owned models after they ship and know how to keep them healthy. Full Lifecycle Delivery (MLOps): Comfortable delivering the end to end production lifecycle - model training, versioning, monitoring, and champion/challenger experimentation - without relying on a dedicated ML engineering team to carry that responsibility. GenAI & LLM Expertise: Hands on experience building LLM powered solutions that deliver measurable business value. You understand how to apply, evaluate, and extend these tools - and you're honest about where they fall short. Technical Depth: Solid experience in a cloud ML environment with software engineering principles - version control, code reviews, unit testing, and familiarity with containerisation. Quantitative Rigour: Strong foundation in statistical evaluation and experiment design. You can define and defend success metrics, and you know when a model is degrading and what to do about it. Bonus Experience with VertexAI TOOLS & TECHNOLOGIES Languages: Python, SQL Data & Transformation: dbt, Snowflake, BigQuery Visualisation & BI: Looker Engineering & MLOps: Docker, GitHub Workflow & Orchestration: Vertex AI Pipelines (GCP), Kubeflow LLMs & GenAI: Gemini API, Claude API INTERVIEW PROCESS Step 1: People Team Screening Call (30 min) Step 2: Hiring Manager Call: Experience (45 min) Step 3: Technical Task: covering both Modelling & Production with Presentation (60 min + Task) Step 4: Values Interview (45 min) WHAT'S IN IT FOR YOU Hybrid working Competitive salary to fund that dream holiday to Bali Matched pension contributions for a peaceful retirement Share options - when we thrive, so do you! Vitality Private Healthcare, for peace of mind, plus eyecare vouchers Life Assurance for (even more) peace of mind Monthly coaching sessions with Spill - our mental wellbeing partner Enhanced holiday package, plus Bank Holidays 28 days annual leave 1 day for your wedding 1 day off when you move house - because moving is hard enough without work! For your third year anniversary, get 30 days of annual leave per year For your tenth year anniversary, get 35 days of annual leave per year Option to buy 3 extra days of holiday per year Work from abroad for a month Inclusive parental, partner and shared parental leave, fertility treatment and pregnancy loss policies Bubble childcare support and discounted nanny fees for little ones The latest tech (Macbook or Surface) to power your gif sending talents Up to £500/€550 home office allowance for that massage chair you've been talking about Generous learning and development budget to help you master your craft Regular social events: tech lunches, coffee with the exec sessions, lunch 8 learns, book clubs, social events/anything else you pester us for Refer a friend, get paid. Repeat for infinite money Diversity and inclusion is an integral part of our culture. We know that diverse teams are strong teams, so we welcome those with alternative identities, backgrounds, and experiences to apply for this position. We make recruiting decisions based on experience, skills and potential, so all our applicants are treated fairly and equally.
25/07/2026
Full time
OUR MISSION To become the car-changing destination of choice. By combining technology, media and deep automotive expertise, we've turned how people buy, sell, advertise and lease cars on its head. What started as a simple reviews site is now one of the largest online car-changing destinations in Europe. Last year alone we grew over 50% with nearly £3bn worth of cars bought on site, while £1.8bn of cars were listed for sale through our Sell My Car service. In 2024 we went big and acquired Autovia - creators of AutoExpress and Evo magazines - doubling our audience overnight. Together we now have one of the biggest YouTube channels in the world with almost 10m subscribers and over 1.1 billion annual views, while we sell 1.2 million print copies of our magazines and have an annual web content reach over 350million. And we're a long way from done! THE ROLE We're looking for a Senior Data Scientist to join our award-winning Data Science team at a pivotal moment. Carwow operates a two-sided marketplace - connecting car buyers and sellers at scale - and data science sits at the heart of how we make that marketplace smarter, faster, and more valuable for everyone in it. In fact, we recently won GenAI initiative of the Year at the British Data Awards. This is a hands on, high ownership role working centrally across the business. You'll partner with teams spanning Commercial, Marketing, Product, Finance, Engineering and Operations - developing and deploying ML and AI solutions that drive outcomes across both sides of our marketplace. The problems you'll work on are genuinely varied: pricing models, propensity and demand signals that sharpen marketing spend, personalised recommendations for our web product and CRM, and LLM powered solutions for operational challenges like document verification. You'll translate ambiguous business problems into structured, production ready solutions - and you'll be expected to deliver them end to end, from first principles through to being deployment ready and beyond. WHAT YOU'LL BE DOING End-to-End ML & AI Delivery: Lead data science initiatives from problem framing through to deployment, monitoring, and iteration - delivering the full production lifecycle. With no dedicated ML engineering function, you'll be responsible for ensuring your solutions are robust, scalable, and performing in the real world long after they ship. GenAI & LLM Application: Design and build LLM-powered solutions where they create genuine business value - document processing, intelligent search, content understanding, and beyond. Apply them alongside classical ML with clear judgement about where each approach earns its place. Commercial Impact: Connect your work directly to business outcomes. Whether you're building a model to improve marketing efficiency, a pricing signal to sharpen commercial decisions, or a recommendation engine to increase conversion - you understand the business lever you're pulling and design your solutions accordingly. Prototyping & Experimentation: Move fast to test ideas before committing to full scale development. Define rigorous success metrics upfront, validate honestly, and know when to double down and when to walk away. Cross Functional Partnership: Work closely with Commercial, Marketing, Product, Finance, Engineering and Operations stakeholders to understand problems deeply before reaching for a solution. Translate findings into clear, actionable narratives for both technical and non-technical audiences. Standards & Craft: Contribute to shared best practices, documentation, and ways of working that raise the bar for the data science function - and help more junior team members grow alongside you. Drive continued adoption of AI capabilities to drive efficiencies, automation and constantly leverage new capabilities. WHAT YOU'LL NEED Please note: We know that no candidate will be the perfect match for all we've listed in this posting, so we'd encourage you to apply if you feel you're close to the brief but not an exact match. Ideally you'll have Commercial Mindset: You think about business impact first. You understand how your models connect to revenue, efficiency, or customer outcomes - and you use that to prioritise, scope, and communicate your work. Stakeholder Partnership: Proven ability to work with commercial, marketing, and product stakeholders - translating business problems into well scoped solutions and communicating technical solutions, challenges and outcomes clearly at all levels. Sound Judgement: You navigate the tooling landscape with clear eyes - knowing when classical ML is right, when GenAI unlocks something new, and when a simpler solution is the more honest answer. Strong instincts for scalability, reliability, and explainability. Bonus Marketplace or Two Sided Platform Experience: Understanding of supply/demand dynamics and how data science creates leverage in a marketplace context. TEHCNICAL SKILLSET Proven ML Experience: A strong track record of building, deploying, and maintaining ML models in Python in a production environment - not just notebooks. You've owned models after they ship and know how to keep them healthy. Full Lifecycle Delivery (MLOps): Comfortable delivering the end to end production lifecycle - model training, versioning, monitoring, and champion/challenger experimentation - without relying on a dedicated ML engineering team to carry that responsibility. GenAI & LLM Expertise: Hands on experience building LLM powered solutions that deliver measurable business value. You understand how to apply, evaluate, and extend these tools - and you're honest about where they fall short. Technical Depth: Solid experience in a cloud ML environment with software engineering principles - version control, code reviews, unit testing, and familiarity with containerisation. Quantitative Rigour: Strong foundation in statistical evaluation and experiment design. You can define and defend success metrics, and you know when a model is degrading and what to do about it. Bonus Experience with VertexAI TOOLS & TECHNOLOGIES Languages: Python, SQL Data & Transformation: dbt, Snowflake, BigQuery Visualisation & BI: Looker Engineering & MLOps: Docker, GitHub Workflow & Orchestration: Vertex AI Pipelines (GCP), Kubeflow LLMs & GenAI: Gemini API, Claude API INTERVIEW PROCESS Step 1: People Team Screening Call (30 min) Step 2: Hiring Manager Call: Experience (45 min) Step 3: Technical Task: covering both Modelling & Production with Presentation (60 min + Task) Step 4: Values Interview (45 min) WHAT'S IN IT FOR YOU Hybrid working Competitive salary to fund that dream holiday to Bali Matched pension contributions for a peaceful retirement Share options - when we thrive, so do you! Vitality Private Healthcare, for peace of mind, plus eyecare vouchers Life Assurance for (even more) peace of mind Monthly coaching sessions with Spill - our mental wellbeing partner Enhanced holiday package, plus Bank Holidays 28 days annual leave 1 day for your wedding 1 day off when you move house - because moving is hard enough without work! For your third year anniversary, get 30 days of annual leave per year For your tenth year anniversary, get 35 days of annual leave per year Option to buy 3 extra days of holiday per year Work from abroad for a month Inclusive parental, partner and shared parental leave, fertility treatment and pregnancy loss policies Bubble childcare support and discounted nanny fees for little ones The latest tech (Macbook or Surface) to power your gif sending talents Up to £500/€550 home office allowance for that massage chair you've been talking about Generous learning and development budget to help you master your craft Regular social events: tech lunches, coffee with the exec sessions, lunch 8 learns, book clubs, social events/anything else you pester us for Refer a friend, get paid. Repeat for infinite money Diversity and inclusion is an integral part of our culture. We know that diverse teams are strong teams, so we welcome those with alternative identities, backgrounds, and experiences to apply for this position. We make recruiting decisions based on experience, skills and potential, so all our applicants are treated fairly and equally.
Senior AI Engineer Manager/Associate Director Capital Markets Location: Manchester Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13116 Senior AI Engineering professionals are required to support the design, build and delivery of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI engineering and enterprise solution delivery within complex environments. You will play a key role in shaping AI strategy, leading teams and delivering enterprise AI solutions, helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building and deploying AI prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting AI deployment, serving patterns, evaluation frameworks and integration design Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data privacy and regulatory risks Contributing to technical documentation, solution design and delivery planning Supporting AI implementation and scaling initiatives across complex environments Leading and developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing or supporting evaluation frameworks for AI or agentic systems Experience working with modern data architectures and cloud platforms Understanding of AI risk, governance, security and regulatory considerations Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI engineering professional who wants to work on high impact AI and data transformation programmes within complex financial services environments.
25/07/2026
Full time
Senior AI Engineer Manager/Associate Director Capital Markets Location: Manchester Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13116 Senior AI Engineering professionals are required to support the design, build and delivery of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI engineering and enterprise solution delivery within complex environments. You will play a key role in shaping AI strategy, leading teams and delivering enterprise AI solutions, helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building and deploying AI prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting AI deployment, serving patterns, evaluation frameworks and integration design Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data privacy and regulatory risks Contributing to technical documentation, solution design and delivery planning Supporting AI implementation and scaling initiatives across complex environments Leading and developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing or supporting evaluation frameworks for AI or agentic systems Experience working with modern data architectures and cloud platforms Understanding of AI risk, governance, security and regulatory considerations Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI engineering professional who wants to work on high impact AI and data transformation programmes within complex financial services environments.
Job title: Machine Learning Engineer Locations: Manchester or Haywards Heath (hybrid working) Role overview Markerstudy Group are looking for a Machine Learning Engineer to help take leading-edge and novel insurance risk modelling and pricing techniques and participate in creating fully automated machine learning pipelines. Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1 billion. Most of Markerstudy s business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury s, O2, Halifax, AA, Saga and Lloyds Bank to list a few. As a Machine Learning Engineer, you will use your skills to: Tune machine learning methods to best leverage our state-of-the-art processing capabilities Deploy and maintain machine learning methods in a DevOps / MLOps based machine learning environment Create robust high-quality code using test-driven development (TDD) techniques and adhering to the SOLID coding standards Your work will enable sustained improvements to products, prices and processes giving Markerstudy a critical advantage in the increasingly competitive insurance market by minimizing the development to deployment and monitoring stages of the ML lifecycle through automation. You will also be responsible for refining, tuning, deploying and maintaining machine learning methods in our machine learning pipeline by using robust test-driven development (TDD) approaches to maximise performance and robustness, and improve company performance and our customer-centric offerings across Motor, Home and Commercial Lines businesses. The successful candidate will also enjoy opportunities for leading, coaching, and mentoring more junior ML Engineers. Key Responsibilities: Report and communicate with Senior Stakeholders, such as the Head of Data Science and Machine Learning and Director of Technical Underwriting Propose, proof-of-concept, develop, and deliver novel machine learning processes that automate current manual processes, and leverage DevOps and MLOps software. Work in a collaborative environment with data science to help deploy machine learning methods that are state-of-the-art, robust, and future extensible. Tune machine learning methods for optimal performance. Deploy and maintain machine learning methods in our machine learning pipeline using robust test-driven development (TDD) coding approaches, using the SOLID software development principles. Actively contribute to creating a culture of coding and data excellence Implement efficient solutions across a range of markets, including Private Motor, Commercial Vehicle, Bike, Taxi, and Home Lead and mentor junior machine learning engineers and share best practices Key Skills and Experience: Previous experience in tuning and deploying machine learning methods Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in DevOps and Azure ML, or other MLOps and ML Lifecycle technology stacks, such as AWS, Databricks, Google Cloud, etc. Experience with deploying services in Docker and Kubernetes Experience in creating production grade coding and SOLID programming principles, including test-driven development (TDD) approaches Experience in programming languages (e.g. Python, PySpark, R, SAS, SQL) Experience in source-control software, e.g., GitHub Proficient at communicating results in a concise manner both verbally and written Experience in data and model monitoring is a plus Behaviours: A high level of professional/academic excellence, educated to at least a master s level in a STEM-based or DS / ML / AI / or mathematical discipline Collaborative and team player Logical thinker with a professional and positive attitude Passion to innovate and improve processes
25/07/2026
Full time
Job title: Machine Learning Engineer Locations: Manchester or Haywards Heath (hybrid working) Role overview Markerstudy Group are looking for a Machine Learning Engineer to help take leading-edge and novel insurance risk modelling and pricing techniques and participate in creating fully automated machine learning pipelines. Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1 billion. Most of Markerstudy s business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury s, O2, Halifax, AA, Saga and Lloyds Bank to list a few. As a Machine Learning Engineer, you will use your skills to: Tune machine learning methods to best leverage our state-of-the-art processing capabilities Deploy and maintain machine learning methods in a DevOps / MLOps based machine learning environment Create robust high-quality code using test-driven development (TDD) techniques and adhering to the SOLID coding standards Your work will enable sustained improvements to products, prices and processes giving Markerstudy a critical advantage in the increasingly competitive insurance market by minimizing the development to deployment and monitoring stages of the ML lifecycle through automation. You will also be responsible for refining, tuning, deploying and maintaining machine learning methods in our machine learning pipeline by using robust test-driven development (TDD) approaches to maximise performance and robustness, and improve company performance and our customer-centric offerings across Motor, Home and Commercial Lines businesses. The successful candidate will also enjoy opportunities for leading, coaching, and mentoring more junior ML Engineers. Key Responsibilities: Report and communicate with Senior Stakeholders, such as the Head of Data Science and Machine Learning and Director of Technical Underwriting Propose, proof-of-concept, develop, and deliver novel machine learning processes that automate current manual processes, and leverage DevOps and MLOps software. Work in a collaborative environment with data science to help deploy machine learning methods that are state-of-the-art, robust, and future extensible. Tune machine learning methods for optimal performance. Deploy and maintain machine learning methods in our machine learning pipeline using robust test-driven development (TDD) coding approaches, using the SOLID software development principles. Actively contribute to creating a culture of coding and data excellence Implement efficient solutions across a range of markets, including Private Motor, Commercial Vehicle, Bike, Taxi, and Home Lead and mentor junior machine learning engineers and share best practices Key Skills and Experience: Previous experience in tuning and deploying machine learning methods Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in DevOps and Azure ML, or other MLOps and ML Lifecycle technology stacks, such as AWS, Databricks, Google Cloud, etc. Experience with deploying services in Docker and Kubernetes Experience in creating production grade coding and SOLID programming principles, including test-driven development (TDD) approaches Experience in programming languages (e.g. Python, PySpark, R, SAS, SQL) Experience in source-control software, e.g., GitHub Proficient at communicating results in a concise manner both verbally and written Experience in data and model monitoring is a plus Behaviours: A high level of professional/academic excellence, educated to at least a master s level in a STEM-based or DS / ML / AI / or mathematical discipline Collaborative and team player Logical thinker with a professional and positive attitude Passion to innovate and improve processes
We'd all like amazing work to do, and real work life balance. That's waiting for you at Sainsbury's. Think about the scale it takes to feed the nation. The level of data, transactions and variety involved. Then you'll realise this is a modern software engineering environment, because it has to be. We've made significant investment in the standards and principles that shape how we work. We iterate, learn, experiment and champion ways of working such as Agile, Scrum and XP. So you can look forward to exciting opportunities across everything from AI to reusable tech. Job Title: Senior Machine Learning Engineer Location: London Department: Media Agency Job Overview As a Senior Machine Learning Engineer, you will play a pivotal role in designing, building and optimising a Machine Learning system for Advert Classification. We are looking for a Machine Learning leader who is competent across modern ML tooling, methodologies and design practices, whilst also being able to design hybrid systems that integrate LLMs. The Machine Learning lead is expected to lead the ML design and build lifecycle, arriving at a reliable and performant system, supporting a team of Data Scientists in the delivery. Systematic evaluation of performance with data is a critical part of our ML initiatives and as a result the ML Lead is expected to drive the strategy and operationalise automatic machine evaluation with metrics and best practice MLOps. You will partner with Data Scientists and Software Engineers, to ensure the system is reliable, performant and production ready. You will also contribute to engineering excellence, across Machine Learning and MLOps, by driving best practices, mentoring other engineers, and shaping the technical direction of data and ML workflows across our domain. Key Responsibilities Lead the design and build of high quality, scalable and reusable Machine Learning systems using Sainsbury's engineering standards and best practices. Design and optimise Machine Learning modules for Advert classification, applying the ML Lifecycle and best practice in model selection and development. Lead the design and implementation of supporting Machine Learning Operations, applying best in class approaches to data versions, model re training and data observability. Implement automation tools and frameworks for experiment tracking, data and model observability to streamline the deployment and monitoring of machine learning models in production. Lead the system evaluation methodology, including the evaluation strategy, data generation and evaluation metrics. Provide guidance to mid Data Scientists on best practice and methodological choices, when optimising machine learning modules and the system, overall. Provide technical guidance on best practices and emerging technologies in data engineering and machine learning and helping to enhance their skills and career growth. Collaborate and support with data scientists across the lifecycle, including EDA, data transformation, model selection, feature engineering, model selection. Optimise data processing workflows and storage solutions to improve performance and reduce costs. Work closely with cross functional teams, including software engineering and product management, to deliver data solutions that meet business needs. Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews. Innovation and Continuous Improvement: Foster a collaborative and inclusive team environment that encourages continuous learning and improvement. Essential Criteria 6-10 years experience designing and building Machine Learning systems end to end, including strong experience implementing MLOps. Strong understanding of modern Machine Learning methodologies, Data Science and accompanying algorithms. Additionally, good experience integrating LLMs as hybrid AI ML systems. Academic background with at least a BSc in Computer Science. Desirable Criteria Experience in modern Computer Vision, having built image detection systems end to end. Strong understanding of ML deployment and management on modern Cloud platforms, specifically MS Azure and AWS. Strong analytical and problem solving skills. Excellent communication skills, able to explain complex concepts to non technical stakeholders. Ability to work independently as well as collaboratively within cross functional teams. Expectations Leadership and Communication Provide technical direction, set standards, and lead by example in science and engineering excellence. Facilitate Scrum ceremonies when required (stand ups, planning, grooming). Communicate clearly and transparently, creating an inclusive environment where diverse opinions are encouraged. Collaborative Attitude Strong team player with a collaborative approach to working with cross functional teams within the Media Agency. Open to feedback and willing to provide constructive criticism to others. Be available for the team, responding within a reasonable time frame and if not possible clearly signpost alternative contacts who can guide. Building a community across Media Agency. Contribute to a positive and inclusive atmosphere within the team. Knowledge Sharing and Empowerment Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels. Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap. Deliver Through Others Share domain expertise proactively and help establish the engineering direction for the team. Support spikes, POCs and early investigative work. Encourage strong developer behaviors (e.g., cameras on for collaboration, documentation, active presence). Lead by example in communication, visibility, accountability and role modeling Sainsbury's values. "We are committed to being a truly inclusive retailer, so you'll be welcomed whoever you are and wherever you work. Around here, there's always the chance to try something new - whether that's as part of an evolving team or somewhere else across the business - and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working. When you join our team, we'll also offer you an amazing range of benefits. Here are some of them: Starting off with colleague discount, you'll be able to get 10% off at Sainsbury's, Argos, TU and Habitat after 4 weeks. This increases to 15% off at Sainsbury's every Friday and Saturday and 15% off at Argos every pay day. We've also got you covered for your future with our pensions scheme and life cover. You'll also be able to share in our success as you may be eligible for a performance related bonus of up to 20% of salary, depending on how we perform. Your wellbeing is important to us too. You'll receive an annual holiday allowance, and you can buy additional holiday. We also offer other benefits that will help your money go further such as season ticket loans, interest free car loan of up to £10k, cycle to work scheme, health cash plans, pay advance (where you can access some of your pay before pay day) as well access to a great range of discounts from hundreds of other retailers. And if you ever need it there is also an Employee Assistance Programme, you will also be eligible for private healthcare too. Moments that matter are as important to us as they are to you which is why we give up to 26 weeks' pay for maternity or adoption leave and up to 4 weeks' pay for paternity leave. Please see for a range of our benefits (note, length of service and eligibility criteria may apply)."
24/07/2026
Full time
We'd all like amazing work to do, and real work life balance. That's waiting for you at Sainsbury's. Think about the scale it takes to feed the nation. The level of data, transactions and variety involved. Then you'll realise this is a modern software engineering environment, because it has to be. We've made significant investment in the standards and principles that shape how we work. We iterate, learn, experiment and champion ways of working such as Agile, Scrum and XP. So you can look forward to exciting opportunities across everything from AI to reusable tech. Job Title: Senior Machine Learning Engineer Location: London Department: Media Agency Job Overview As a Senior Machine Learning Engineer, you will play a pivotal role in designing, building and optimising a Machine Learning system for Advert Classification. We are looking for a Machine Learning leader who is competent across modern ML tooling, methodologies and design practices, whilst also being able to design hybrid systems that integrate LLMs. The Machine Learning lead is expected to lead the ML design and build lifecycle, arriving at a reliable and performant system, supporting a team of Data Scientists in the delivery. Systematic evaluation of performance with data is a critical part of our ML initiatives and as a result the ML Lead is expected to drive the strategy and operationalise automatic machine evaluation with metrics and best practice MLOps. You will partner with Data Scientists and Software Engineers, to ensure the system is reliable, performant and production ready. You will also contribute to engineering excellence, across Machine Learning and MLOps, by driving best practices, mentoring other engineers, and shaping the technical direction of data and ML workflows across our domain. Key Responsibilities Lead the design and build of high quality, scalable and reusable Machine Learning systems using Sainsbury's engineering standards and best practices. Design and optimise Machine Learning modules for Advert classification, applying the ML Lifecycle and best practice in model selection and development. Lead the design and implementation of supporting Machine Learning Operations, applying best in class approaches to data versions, model re training and data observability. Implement automation tools and frameworks for experiment tracking, data and model observability to streamline the deployment and monitoring of machine learning models in production. Lead the system evaluation methodology, including the evaluation strategy, data generation and evaluation metrics. Provide guidance to mid Data Scientists on best practice and methodological choices, when optimising machine learning modules and the system, overall. Provide technical guidance on best practices and emerging technologies in data engineering and machine learning and helping to enhance their skills and career growth. Collaborate and support with data scientists across the lifecycle, including EDA, data transformation, model selection, feature engineering, model selection. Optimise data processing workflows and storage solutions to improve performance and reduce costs. Work closely with cross functional teams, including software engineering and product management, to deliver data solutions that meet business needs. Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews. Innovation and Continuous Improvement: Foster a collaborative and inclusive team environment that encourages continuous learning and improvement. Essential Criteria 6-10 years experience designing and building Machine Learning systems end to end, including strong experience implementing MLOps. Strong understanding of modern Machine Learning methodologies, Data Science and accompanying algorithms. Additionally, good experience integrating LLMs as hybrid AI ML systems. Academic background with at least a BSc in Computer Science. Desirable Criteria Experience in modern Computer Vision, having built image detection systems end to end. Strong understanding of ML deployment and management on modern Cloud platforms, specifically MS Azure and AWS. Strong analytical and problem solving skills. Excellent communication skills, able to explain complex concepts to non technical stakeholders. Ability to work independently as well as collaboratively within cross functional teams. Expectations Leadership and Communication Provide technical direction, set standards, and lead by example in science and engineering excellence. Facilitate Scrum ceremonies when required (stand ups, planning, grooming). Communicate clearly and transparently, creating an inclusive environment where diverse opinions are encouraged. Collaborative Attitude Strong team player with a collaborative approach to working with cross functional teams within the Media Agency. Open to feedback and willing to provide constructive criticism to others. Be available for the team, responding within a reasonable time frame and if not possible clearly signpost alternative contacts who can guide. Building a community across Media Agency. Contribute to a positive and inclusive atmosphere within the team. Knowledge Sharing and Empowerment Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels. Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap. Deliver Through Others Share domain expertise proactively and help establish the engineering direction for the team. Support spikes, POCs and early investigative work. Encourage strong developer behaviors (e.g., cameras on for collaboration, documentation, active presence). Lead by example in communication, visibility, accountability and role modeling Sainsbury's values. "We are committed to being a truly inclusive retailer, so you'll be welcomed whoever you are and wherever you work. Around here, there's always the chance to try something new - whether that's as part of an evolving team or somewhere else across the business - and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working. When you join our team, we'll also offer you an amazing range of benefits. Here are some of them: Starting off with colleague discount, you'll be able to get 10% off at Sainsbury's, Argos, TU and Habitat after 4 weeks. This increases to 15% off at Sainsbury's every Friday and Saturday and 15% off at Argos every pay day. We've also got you covered for your future with our pensions scheme and life cover. You'll also be able to share in our success as you may be eligible for a performance related bonus of up to 20% of salary, depending on how we perform. Your wellbeing is important to us too. You'll receive an annual holiday allowance, and you can buy additional holiday. We also offer other benefits that will help your money go further such as season ticket loans, interest free car loan of up to £10k, cycle to work scheme, health cash plans, pay advance (where you can access some of your pay before pay day) as well access to a great range of discounts from hundreds of other retailers. And if you ever need it there is also an Employee Assistance Programme, you will also be eligible for private healthcare too. Moments that matter are as important to us as they are to you which is why we give up to 26 weeks' pay for maternity or adoption leave and up to 4 weeks' pay for paternity leave. Please see for a range of our benefits (note, length of service and eligibility criteria may apply)."
Senior AI Engineer (Principal Consultant) Location: London (Hybrid) Practice Area: Technology & Engineering Type: Permanent Empower the next frontier of AI with Capco. Shape, build, and deliver future-ready generative systems. The Role We're looking for a Senior AI Engineer (Senior/Principal Consultant) to join our Technology Delivery team. In this role, you'll combine deep expertise in AI/ML engineering and software development to design, build, and deploy advanced generative AI and agentic systems for leading financial services clients. You'll work hands on across the full AI engineering lifecycle, from architecting intelligent multi agent systems to deploying scalable production grade AI applications within enterprise environments. As a senior consultant, you'll also collaborate closely with multidisciplinary teams and client stakeholders to drive innovation, accelerate adoption, and deliver measurable business impact. What You'll Do Architect and develop autonomous AI systems leveraging multi modal large language models across text, image, audio, and video Design and implement agentic workflows using prompt engineering, Retrieval Augmented Generation (RAG), APIs, and enterprise data integrations Fine tune, optimize, and deploy large language and multi modal models with a focus on scalability, reliability, and low latency performance Build scalable MLOps pipelines and cloud native AI applications to support secure, production grade deployments Collaborate with clients and cross functional teams to shape AI engineering strategy and accelerate GenAI adoption across complex environments What We're Looking For Bachelor's degree or higher in Computer Science, Artificial Intelligence, Engineering, or a related STEM discipline Proven hands on experience deploying LLMs and multi modal AI models within enterprise or large scale production environments
24/07/2026
Full time
Senior AI Engineer (Principal Consultant) Location: London (Hybrid) Practice Area: Technology & Engineering Type: Permanent Empower the next frontier of AI with Capco. Shape, build, and deliver future-ready generative systems. The Role We're looking for a Senior AI Engineer (Senior/Principal Consultant) to join our Technology Delivery team. In this role, you'll combine deep expertise in AI/ML engineering and software development to design, build, and deploy advanced generative AI and agentic systems for leading financial services clients. You'll work hands on across the full AI engineering lifecycle, from architecting intelligent multi agent systems to deploying scalable production grade AI applications within enterprise environments. As a senior consultant, you'll also collaborate closely with multidisciplinary teams and client stakeholders to drive innovation, accelerate adoption, and deliver measurable business impact. What You'll Do Architect and develop autonomous AI systems leveraging multi modal large language models across text, image, audio, and video Design and implement agentic workflows using prompt engineering, Retrieval Augmented Generation (RAG), APIs, and enterprise data integrations Fine tune, optimize, and deploy large language and multi modal models with a focus on scalability, reliability, and low latency performance Build scalable MLOps pipelines and cloud native AI applications to support secure, production grade deployments Collaborate with clients and cross functional teams to shape AI engineering strategy and accelerate GenAI adoption across complex environments What We're Looking For Bachelor's degree or higher in Computer Science, Artificial Intelligence, Engineering, or a related STEM discipline Proven hands on experience deploying LLMs and multi modal AI models within enterprise or large scale production environments
Machine Learning Software Engineer, Research London, United Kingdom About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations - empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. Note: We are currently recruiting for multiple positions across different levels, however please only apply for the role that best aligns with your skillset and career goals. What you will do Work closely with our research scientists and simulation engineers to build and deliver models that address real-world physics and engineering problems. Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain. Transform prototype model implementations to robust and optimised implementations. Implement distributed training architectures (e.g., data parallelism, parameter server, etc.) for multi-node/multi-GPU training and explore federated learning capacity using cloud (e.g., AWS, Azure, GCP) and on-premise services. Work with research scientists to design, build and scale foundation models for science and engineering; helping to scale and optimise model training to large data and multi-GPU cloud compute. Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success. Own Research work-streams at different levels, depending on seniority. Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems. Work at the intersection of data science and software engineering to translate the results of our Research into re-usable libraries, tooling and products. Foster a nurturing environment for colleagues with less experience in ML / Engineering for them to grow and you to mentor. What you bring to the table Enthusiasm about developing machine learning solutions, especially deep learning and/or probabilistic methods, and associated supporting software solutions for science and engineering. Ability to work autonomously and scope and effectively deliver projects across a variety of domains. Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly. Excellent collaboration and communication skills - with teams and customers alike. MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or a related field, with a record of experience in any of the following: Scientific computing High-performance computing (CPU / GPU clusters) Parallelised / distributed training for large / foundation models Ideally >2 years of experience in a data-driven role in a professional setting, with exposure to: Scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus) Distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton) Cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications C/C++ for computer vision, geometry processing, or scientific computing Software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) Container-isation and orchestration (Docker, Kubernetes, Slurm) Writing pipelines and experiment environments, including running experiments in pipelines in a systematic way What we offer Build what actually matters Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind. Learn alongside exceptional people Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you're ambitious, thoughtful, and driven by impact, you'll feel at home. Influence over hierarchy We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn't just welcomed, it's expected. Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person. And it doesn't stop there Equity options - share meaningfully in the company you're helping to build. 10% employer pension contribution - because investing in future matters. Free office lunches - to keep you energised and focused. Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most. YellowNest nursery scheme - to help working parents manage childcare costs. 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters. Private medical insurance - 100% employee cover, giving you complete peace of mind. Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing. Eye tests - because good work depends on good health. Personal development - dedicated support for learning, development, and leveling up over time. Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it. Bike2Work scheme and Season ticket loan - to make getting to work easier and greener. Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric. We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics. We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
24/07/2026
Full time
Machine Learning Software Engineer, Research London, United Kingdom About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations - empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. Note: We are currently recruiting for multiple positions across different levels, however please only apply for the role that best aligns with your skillset and career goals. What you will do Work closely with our research scientists and simulation engineers to build and deliver models that address real-world physics and engineering problems. Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain. Transform prototype model implementations to robust and optimised implementations. Implement distributed training architectures (e.g., data parallelism, parameter server, etc.) for multi-node/multi-GPU training and explore federated learning capacity using cloud (e.g., AWS, Azure, GCP) and on-premise services. Work with research scientists to design, build and scale foundation models for science and engineering; helping to scale and optimise model training to large data and multi-GPU cloud compute. Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success. Own Research work-streams at different levels, depending on seniority. Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems. Work at the intersection of data science and software engineering to translate the results of our Research into re-usable libraries, tooling and products. Foster a nurturing environment for colleagues with less experience in ML / Engineering for them to grow and you to mentor. What you bring to the table Enthusiasm about developing machine learning solutions, especially deep learning and/or probabilistic methods, and associated supporting software solutions for science and engineering. Ability to work autonomously and scope and effectively deliver projects across a variety of domains. Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly. Excellent collaboration and communication skills - with teams and customers alike. MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or a related field, with a record of experience in any of the following: Scientific computing High-performance computing (CPU / GPU clusters) Parallelised / distributed training for large / foundation models Ideally >2 years of experience in a data-driven role in a professional setting, with exposure to: Scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus) Distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton) Cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications C/C++ for computer vision, geometry processing, or scientific computing Software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) Container-isation and orchestration (Docker, Kubernetes, Slurm) Writing pipelines and experiment environments, including running experiments in pipelines in a systematic way What we offer Build what actually matters Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind. Learn alongside exceptional people Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you're ambitious, thoughtful, and driven by impact, you'll feel at home. Influence over hierarchy We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn't just welcomed, it's expected. Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person. And it doesn't stop there Equity options - share meaningfully in the company you're helping to build. 10% employer pension contribution - because investing in future matters. Free office lunches - to keep you energised and focused. Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most. YellowNest nursery scheme - to help working parents manage childcare costs. 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters. Private medical insurance - 100% employee cover, giving you complete peace of mind. Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing. Eye tests - because good work depends on good health. Personal development - dedicated support for learning, development, and leveling up over time. Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it. Bike2Work scheme and Season ticket loan - to make getting to work easier and greener. Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric. We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics. We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
About The Role We're looking for a talented Senior Data Scientist to join our growing AI Squad within our Technology division, supporting the Rescue and Recovery operations. As a Senior Data Scientist, you'll play a key role in designing and deploying innovative solutions, working across multiple projects and collaborating with cross functional teams to turn data into actionable insight and real world impact. This is an exciting opportunity to shape the future of roadside operations by applying advanced analytics and machine learning to drive meaningful improvements in operational efficiency and customer experience. The role is suitable for an individual who brings a strong problem solving mindset, with a natural curiosity and the ability to approach challenges creatively and analytically. You'll ideally have hands on experience in experimenting, testing, and trialling new approaches or technologies to validate ideas and drive continuous improvement. This is a hybrid role, working 2 days a week from our Bradley Stoke, Bescot, or Salford offices and 3 days a week from home offering flexibility while being part of a dynamic and supportive team. Benefits Earnings That Motivate - enjoy a competitive salary plus automatic enrolment in our "Owning It Together" Colleague Share Scheme. Tools to Drive Your Future - get started with a free RAC Ultimate Complete Breakdown Service from day one, plus access to a car salary sacrifice scheme (including electric vehicle options) after 12 months. Time Off That Matters - enjoy 25 days annual leave, plus bank holidays, paid family leave, flexible schedules, and practical resources to help navigate personal commitments. Financial Security & Perks - pension scheme with up to 6.5% matched contributions and life assurance cover up to 4 salary (10 optional with flex benefits). Wellbeing That Works for You - our 24/7 confidential support service is available to you and household members aged 16+. Extras That Make a Difference - access to Orange Savings, an exclusive discount portal, and automatic entry into the Colleague Share Scheme after probation. How We Work End to end ownership from exploration to production deployment Close collaboration with Data Engineering and Software teams CI/CD pipelines and version controlled experimentation Model monitoring, evaluation, and continuous improvement Cloud native development using Azure What you'll do Analyse historical and real time data to identify trends, inefficiencies, and optimisation opportunities Develop and deploy cutting edge machine learning models, focusing on operational performance and resource optimisation Enhance real time decision making through advanced analytics and AI solutions Collaborate with Data Engineering teams to ensure high quality data pipelines and model readiness Partner with Product Managers and Software Engineers to integrate models into production systems Validate, monitor, and continuously improve models based on business feedback Communicate insights clearly to stakeholders, translating complex data into business value Contribute to code quality through reviews and maintain well documented, scalable solutions Stay up to date with emerging trends in machine learning, AI, and cloud technologies (particularly Azure) Support the development of data science best practices and standards across the organisation AI & LLM Applications Intelligent triage support tools for customer interactions Knowledge retrieval systems for operational teams Automated insight generation and decision support What you'll need Hands on experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit learn) Strong Python skills for data analysis, modelling, and development Experience working with large language models (LLMs), including prompt engineering, fine tuning, and evaluation Solid SQL and Snowflake knowledge, with experience on relational databases Understanding of version control (e.g., Git) and exposure to MLOps practices Experience working with cloud platforms, ideally Azure Strong problem solving skills and the ability to evaluate a range of solution approaches Excellent communication skills, with the ability to present technical concepts to non technical audiences Experience working in Agile environments Degree in Engineering, Sciences, Data Science, Statistics, or a related field
24/07/2026
Full time
About The Role We're looking for a talented Senior Data Scientist to join our growing AI Squad within our Technology division, supporting the Rescue and Recovery operations. As a Senior Data Scientist, you'll play a key role in designing and deploying innovative solutions, working across multiple projects and collaborating with cross functional teams to turn data into actionable insight and real world impact. This is an exciting opportunity to shape the future of roadside operations by applying advanced analytics and machine learning to drive meaningful improvements in operational efficiency and customer experience. The role is suitable for an individual who brings a strong problem solving mindset, with a natural curiosity and the ability to approach challenges creatively and analytically. You'll ideally have hands on experience in experimenting, testing, and trialling new approaches or technologies to validate ideas and drive continuous improvement. This is a hybrid role, working 2 days a week from our Bradley Stoke, Bescot, or Salford offices and 3 days a week from home offering flexibility while being part of a dynamic and supportive team. Benefits Earnings That Motivate - enjoy a competitive salary plus automatic enrolment in our "Owning It Together" Colleague Share Scheme. Tools to Drive Your Future - get started with a free RAC Ultimate Complete Breakdown Service from day one, plus access to a car salary sacrifice scheme (including electric vehicle options) after 12 months. Time Off That Matters - enjoy 25 days annual leave, plus bank holidays, paid family leave, flexible schedules, and practical resources to help navigate personal commitments. Financial Security & Perks - pension scheme with up to 6.5% matched contributions and life assurance cover up to 4 salary (10 optional with flex benefits). Wellbeing That Works for You - our 24/7 confidential support service is available to you and household members aged 16+. Extras That Make a Difference - access to Orange Savings, an exclusive discount portal, and automatic entry into the Colleague Share Scheme after probation. How We Work End to end ownership from exploration to production deployment Close collaboration with Data Engineering and Software teams CI/CD pipelines and version controlled experimentation Model monitoring, evaluation, and continuous improvement Cloud native development using Azure What you'll do Analyse historical and real time data to identify trends, inefficiencies, and optimisation opportunities Develop and deploy cutting edge machine learning models, focusing on operational performance and resource optimisation Enhance real time decision making through advanced analytics and AI solutions Collaborate with Data Engineering teams to ensure high quality data pipelines and model readiness Partner with Product Managers and Software Engineers to integrate models into production systems Validate, monitor, and continuously improve models based on business feedback Communicate insights clearly to stakeholders, translating complex data into business value Contribute to code quality through reviews and maintain well documented, scalable solutions Stay up to date with emerging trends in machine learning, AI, and cloud technologies (particularly Azure) Support the development of data science best practices and standards across the organisation AI & LLM Applications Intelligent triage support tools for customer interactions Knowledge retrieval systems for operational teams Automated insight generation and decision support What you'll need Hands on experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit learn) Strong Python skills for data analysis, modelling, and development Experience working with large language models (LLMs), including prompt engineering, fine tuning, and evaluation Solid SQL and Snowflake knowledge, with experience on relational databases Understanding of version control (e.g., Git) and exposure to MLOps practices Experience working with cloud platforms, ideally Azure Strong problem solving skills and the ability to evaluate a range of solution approaches Excellent communication skills, with the ability to present technical concepts to non technical audiences Experience working in Agile environments Degree in Engineering, Sciences, Data Science, Statistics, or a related field
About The Role We're looking for a talented Senior Data Scientist to join our growing AI Squad within our Technology division, supporting the Rescue and Recovery operations. As a Senior Data Scientist, you'll play a key role in designing and deploying innovative solutions, working across multiple projects and collaborating with cross functional teams to turn data into actionable insight and real world impact. This is an exciting opportunity to shape the future of roadside operations by applying advanced analytics and machine learning to drive meaningful improvements in operational efficiency and customer experience. The role is suitable for an individual who brings a strong problem solving mindset, with a natural curiosity and the ability to approach challenges creatively and analytically. You'll ideally have hands on experience in experimenting, testing, and trialling new approaches or technologies to validate ideas and drive continuous improvement. This is a hybrid role, working 2 days a week from our Bradley Stoke, Bescot, or Salford offices and 3 days a week from home offering flexibility while being part of a dynamic and supportive team. Benefits Earnings That Motivate - enjoy a competitive salary plus automatic enrolment in our "Owning It Together" Colleague Share Scheme. Tools to Drive Your Future - get started with a free RAC Ultimate Complete Breakdown Service from day one, plus access to a car salary sacrifice scheme (including electric vehicle options) after 12 months. Time Off That Matters - enjoy 25 days annual leave, plus bank holidays, paid family leave, flexible schedules, and practical resources to help navigate personal commitments. Financial Security & Perks - pension scheme with up to 6.5% matched contributions and life assurance cover up to 4 salary (10 optional with flex benefits). Wellbeing That Works for You - our 24/7 confidential support service is available to you and household members aged 16+. Extras That Make a Difference - access to Orange Savings, an exclusive discount portal, and automatic entry into the Colleague Share Scheme after probation. How We Work End to end ownership from exploration to production deployment Close collaboration with Data Engineering and Software teams CI/CD pipelines and version controlled experimentation Model monitoring, evaluation, and continuous improvement Cloud native development using Azure What you'll do Analyse historical and real time data to identify trends, inefficiencies, and optimisation opportunities Develop and deploy cutting edge machine learning models, focusing on operational performance and resource optimisation Enhance real time decision making through advanced analytics and AI solutions Collaborate with Data Engineering teams to ensure high quality data pipelines and model readiness Partner with Product Managers and Software Engineers to integrate models into production systems Validate, monitor, and continuously improve models based on business feedback Communicate insights clearly to stakeholders, translating complex data into business value Contribute to code quality through reviews and maintain well documented, scalable solutions Stay up to date with emerging trends in machine learning, AI, and cloud technologies (particularly Azure) Support the development of data science best practices and standards across the organisation AI & LLM Applications Intelligent triage support tools for customer interactions Knowledge retrieval systems for operational teams Automated insight generation and decision support What you'll need Hands on experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit learn) Strong Python skills for data analysis, modelling, and development Experience working with large language models (LLMs), including prompt engineering, fine tuning, and evaluation Solid SQL and Snowflake knowledge, with experience on relational databases Understanding of version control (e.g., Git) and exposure to MLOps practices Experience working with cloud platforms, ideally Azure Strong problem solving skills and the ability to evaluate a range of solution approaches Excellent communication skills, with the ability to present technical concepts to non technical audiences Experience working in Agile environments Degree in Engineering, Sciences, Data Science, Statistics, or a related field
24/07/2026
Full time
About The Role We're looking for a talented Senior Data Scientist to join our growing AI Squad within our Technology division, supporting the Rescue and Recovery operations. As a Senior Data Scientist, you'll play a key role in designing and deploying innovative solutions, working across multiple projects and collaborating with cross functional teams to turn data into actionable insight and real world impact. This is an exciting opportunity to shape the future of roadside operations by applying advanced analytics and machine learning to drive meaningful improvements in operational efficiency and customer experience. The role is suitable for an individual who brings a strong problem solving mindset, with a natural curiosity and the ability to approach challenges creatively and analytically. You'll ideally have hands on experience in experimenting, testing, and trialling new approaches or technologies to validate ideas and drive continuous improvement. This is a hybrid role, working 2 days a week from our Bradley Stoke, Bescot, or Salford offices and 3 days a week from home offering flexibility while being part of a dynamic and supportive team. Benefits Earnings That Motivate - enjoy a competitive salary plus automatic enrolment in our "Owning It Together" Colleague Share Scheme. Tools to Drive Your Future - get started with a free RAC Ultimate Complete Breakdown Service from day one, plus access to a car salary sacrifice scheme (including electric vehicle options) after 12 months. Time Off That Matters - enjoy 25 days annual leave, plus bank holidays, paid family leave, flexible schedules, and practical resources to help navigate personal commitments. Financial Security & Perks - pension scheme with up to 6.5% matched contributions and life assurance cover up to 4 salary (10 optional with flex benefits). Wellbeing That Works for You - our 24/7 confidential support service is available to you and household members aged 16+. Extras That Make a Difference - access to Orange Savings, an exclusive discount portal, and automatic entry into the Colleague Share Scheme after probation. How We Work End to end ownership from exploration to production deployment Close collaboration with Data Engineering and Software teams CI/CD pipelines and version controlled experimentation Model monitoring, evaluation, and continuous improvement Cloud native development using Azure What you'll do Analyse historical and real time data to identify trends, inefficiencies, and optimisation opportunities Develop and deploy cutting edge machine learning models, focusing on operational performance and resource optimisation Enhance real time decision making through advanced analytics and AI solutions Collaborate with Data Engineering teams to ensure high quality data pipelines and model readiness Partner with Product Managers and Software Engineers to integrate models into production systems Validate, monitor, and continuously improve models based on business feedback Communicate insights clearly to stakeholders, translating complex data into business value Contribute to code quality through reviews and maintain well documented, scalable solutions Stay up to date with emerging trends in machine learning, AI, and cloud technologies (particularly Azure) Support the development of data science best practices and standards across the organisation AI & LLM Applications Intelligent triage support tools for customer interactions Knowledge retrieval systems for operational teams Automated insight generation and decision support What you'll need Hands on experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit learn) Strong Python skills for data analysis, modelling, and development Experience working with large language models (LLMs), including prompt engineering, fine tuning, and evaluation Solid SQL and Snowflake knowledge, with experience on relational databases Understanding of version control (e.g., Git) and exposure to MLOps practices Experience working with cloud platforms, ideally Azure Strong problem solving skills and the ability to evaluate a range of solution approaches Excellent communication skills, with the ability to present technical concepts to non technical audiences Experience working in Agile environments Degree in Engineering, Sciences, Data Science, Statistics, or a related field
Principal Data Scientist & Machine Learning Researcher Gloucester London Manchester Working with a leading National Security and Cyber organisation, you will help develop advanced AI and machine learning solutions that support critical national security missions. Operating within a mature Agile environment, you'll collaborate closely with customers, engineers, researchers and data scientists to solve complex real-world challenges using cutting-edge AI, machine learning and data science techniques. We have opportunities at all levels from Associate, Senior and Principal levels. Roles can be based in Gloucester, Manchester or London, with hybrid working available (typically 3 days per week on-site). Due to the nature of work in National Infrastructure, candidates must hold an active eDV (enhanced DV) UK Security Clearance. The Opportunity As a Senior Data Scientist & Machine Learning Researcher, you will play a key role in the technical leadership, design and delivery of AI and machine learning projects from concept through to deployment. You'll work within a specialist team of Data Science, AI and Machine Learning experts, driving innovative research, developing advanced solutions and mentoring colleagues across a range of customer and internal R&D programmes. This position offers the opportunity to contribute to genuinely challenging and impactful projects while helping shape future AI capabilities within the national security domain. Key Responsibilities Design, develop and deliver complex machine learning and data science solutions with a high degree of autonomy. Lead technical investigations, research activities and AI/ML development across customer and internal projects. Identify innovative approaches to solving complex technical challenges and contribute to future research directions. Provide technical leadership within project teams and support successful project delivery. Collaborate with multidisciplinary teams, stakeholders and customers to define requirements and develop effective technical solutions. Mentor and support junior team members, helping to develop technical capability across the wider team. Communicate complex technical concepts clearly to both technical and non-technical audiences. Essential Skills & Experience Degree (BSc or above) in Data Science, Machine Learning, Computer Science, Mathematics or a related discipline. Strong Python development experience, including machine learning frameworks such as Hugging Face, TensorFlow and PyTorch. Proven experience delivering machine learning solutions within commercial, research or government environments. Strong understanding of modern AI/ML techniques across areas such as Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP) and Computer Vision. Experience training, fine-tuning and evaluating machine learning and AI models. Ability to undertake technical research and apply findings to real-world challenges. Experience producing high-quality technical documentation, reports or research publications. Previous experience mentoring team members and providing technical leadership. Desirable Skills & Experience MSc or PhD with a strong research background. Experience developing and maintaining robust ML pipelines and MLOps practices. Familiarity with version control, containerisation and environment management tools, including Git and Docker. Experience working within Linux environments and using command-line tooling. Experience deploying and scaling AI/ML solutions into production environments. Cloud platform experience, ideally AWS, although Azure or GCP experience is also valuable. Published research in peer-reviewed journals or conferences. Experience writing technical proposals, bids or research funding submissions. What's on Offer Opportunity to work on highly complex and meaningful national security challenges. Exposure to cutting-edge AI, Machine Learning and Data Science projects. Collaborative environment with experienced researchers, engineers and technical specialists. Clear opportunities for technical development, leadership and career progression. Hybrid working with locations in Gloucester, Manchester or London. Benefits Competitive salary and excellent benefits eDV bonus on top of salary and annual bonus Company bonus scheme Contributory Pension Scheme (up to 10.5% company contribution) 6 times salary 'Life Assurance' with pension 25 days holiday (increasing with service) + statutory public holidays, plus opportunity to buy and sell up to 5 days
23/07/2026
Full time
Principal Data Scientist & Machine Learning Researcher Gloucester London Manchester Working with a leading National Security and Cyber organisation, you will help develop advanced AI and machine learning solutions that support critical national security missions. Operating within a mature Agile environment, you'll collaborate closely with customers, engineers, researchers and data scientists to solve complex real-world challenges using cutting-edge AI, machine learning and data science techniques. We have opportunities at all levels from Associate, Senior and Principal levels. Roles can be based in Gloucester, Manchester or London, with hybrid working available (typically 3 days per week on-site). Due to the nature of work in National Infrastructure, candidates must hold an active eDV (enhanced DV) UK Security Clearance. The Opportunity As a Senior Data Scientist & Machine Learning Researcher, you will play a key role in the technical leadership, design and delivery of AI and machine learning projects from concept through to deployment. You'll work within a specialist team of Data Science, AI and Machine Learning experts, driving innovative research, developing advanced solutions and mentoring colleagues across a range of customer and internal R&D programmes. This position offers the opportunity to contribute to genuinely challenging and impactful projects while helping shape future AI capabilities within the national security domain. Key Responsibilities Design, develop and deliver complex machine learning and data science solutions with a high degree of autonomy. Lead technical investigations, research activities and AI/ML development across customer and internal projects. Identify innovative approaches to solving complex technical challenges and contribute to future research directions. Provide technical leadership within project teams and support successful project delivery. Collaborate with multidisciplinary teams, stakeholders and customers to define requirements and develop effective technical solutions. Mentor and support junior team members, helping to develop technical capability across the wider team. Communicate complex technical concepts clearly to both technical and non-technical audiences. Essential Skills & Experience Degree (BSc or above) in Data Science, Machine Learning, Computer Science, Mathematics or a related discipline. Strong Python development experience, including machine learning frameworks such as Hugging Face, TensorFlow and PyTorch. Proven experience delivering machine learning solutions within commercial, research or government environments. Strong understanding of modern AI/ML techniques across areas such as Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP) and Computer Vision. Experience training, fine-tuning and evaluating machine learning and AI models. Ability to undertake technical research and apply findings to real-world challenges. Experience producing high-quality technical documentation, reports or research publications. Previous experience mentoring team members and providing technical leadership. Desirable Skills & Experience MSc or PhD with a strong research background. Experience developing and maintaining robust ML pipelines and MLOps practices. Familiarity with version control, containerisation and environment management tools, including Git and Docker. Experience working within Linux environments and using command-line tooling. Experience deploying and scaling AI/ML solutions into production environments. Cloud platform experience, ideally AWS, although Azure or GCP experience is also valuable. Published research in peer-reviewed journals or conferences. Experience writing technical proposals, bids or research funding submissions. What's on Offer Opportunity to work on highly complex and meaningful national security challenges. Exposure to cutting-edge AI, Machine Learning and Data Science projects. Collaborative environment with experienced researchers, engineers and technical specialists. Clear opportunities for technical development, leadership and career progression. Hybrid working with locations in Gloucester, Manchester or London. Benefits Competitive salary and excellent benefits eDV bonus on top of salary and annual bonus Company bonus scheme Contributory Pension Scheme (up to 10.5% company contribution) 6 times salary 'Life Assurance' with pension 25 days holiday (increasing with service) + statutory public holidays, plus opportunity to buy and sell up to 5 days
