Our client is building the most advanced AI platform in their market. They help their clients serve customers with unmatched speed and accuracy. They've invested heavily into building the ML stack, partnered with leading universities, and trained models on millions of expert-tagged images. Now, they're scaling globally - and need a world-class Lead Data Scientist to help push the boundaries of computer vision, video analysis, and multimodal LLMs while solving real-world challenges. Role Overview They are looking for an experienced Lead Data Scientist to spearhead machine-learning initiatives, with particular focus on computer vision, large language models, and production ready ML pipelines in Azure. You will act as the technical lead for the team, setting direction, guiding best practices, and ensuring the successful delivery of high-impact AI solutions. Key Responsibilities Develop, train, and deploy computer vision models (object detection, image classification, segmentation, multi-modal learning) Fine-tune, evaluate, and productionise multi-modal LLMs for business applications. Drive experimentation and prototyping of advanced ML/AI techniques Provide technical direction, mentoring, and hands-on guidance to the data science team. Work with engineering, product, and business stakeholders to align ML strategy with business goals. Architect and productionise end-to-end ML pipelines on Azure, while ensuring scalability, reproducibility, and monitoring of deployed models. Requirements 6+ years in data science / ML, with at least 2 years in a technical lead role. Deep experience in training and deploying computer vision models into production Proven track record with LLM fine-tuning, prompt engineering and productionisation Deep experience in MLOps on Azure, including CI/CD, monitoring and scaling pipelines. Strong coding skills in Python, with frameworks such as PyTorch, FastAPI and Azure CLI. ALL APPLICANTS MUST BE FREE TO WORK IN THE UK Exposed Solutions is acting as an employment agency to this client. Please note that no terminology in this advert is intended to discriminate on any grounds, and we confirm that we will gladly accept applications from any person for this role.
01/04/2026
Full time
Our client is building the most advanced AI platform in their market. They help their clients serve customers with unmatched speed and accuracy. They've invested heavily into building the ML stack, partnered with leading universities, and trained models on millions of expert-tagged images. Now, they're scaling globally - and need a world-class Lead Data Scientist to help push the boundaries of computer vision, video analysis, and multimodal LLMs while solving real-world challenges. Role Overview They are looking for an experienced Lead Data Scientist to spearhead machine-learning initiatives, with particular focus on computer vision, large language models, and production ready ML pipelines in Azure. You will act as the technical lead for the team, setting direction, guiding best practices, and ensuring the successful delivery of high-impact AI solutions. Key Responsibilities Develop, train, and deploy computer vision models (object detection, image classification, segmentation, multi-modal learning) Fine-tune, evaluate, and productionise multi-modal LLMs for business applications. Drive experimentation and prototyping of advanced ML/AI techniques Provide technical direction, mentoring, and hands-on guidance to the data science team. Work with engineering, product, and business stakeholders to align ML strategy with business goals. Architect and productionise end-to-end ML pipelines on Azure, while ensuring scalability, reproducibility, and monitoring of deployed models. Requirements 6+ years in data science / ML, with at least 2 years in a technical lead role. Deep experience in training and deploying computer vision models into production Proven track record with LLM fine-tuning, prompt engineering and productionisation Deep experience in MLOps on Azure, including CI/CD, monitoring and scaling pipelines. Strong coding skills in Python, with frameworks such as PyTorch, FastAPI and Azure CLI. ALL APPLICANTS MUST BE FREE TO WORK IN THE UK Exposed Solutions is acting as an employment agency to this client. Please note that no terminology in this advert is intended to discriminate on any grounds, and we confirm that we will gladly accept applications from any person for this role.
ML Engineer £500-£560 The Company They are a well-established consumer technology business with a mission to create a safe, trusted environment for millions of users. Data, experimentation, and scalable engineering are core to how they operate. Their Trust function is expanding, and they are investing heavily in modern ML infrastructure to support rapid growth. You will join a collaborative environment where ML Engineers, Scientists, Backend Engineers, and MLOps specialists work closely to deliver measurable impact. The Role In this role, you will: Design and implement pipelines for training, evaluating, deploying, and monitoring detection models Productionise detection models in partnership with ML Scientists, improving reliability and latency across asynchronous inference workflows Collaborate with backend and product teams to define integration requirements for trust detection services Extend ML infrastructure with MLOps teams, including reproducible training workflows, CI/CD for model deployment, batch and real-time model serving, feature consistency, and monitoring Uphold strong standards around testing, observability, and operational excellence Contribute to a scaling engineering culture where experimentation and measurable outcomes are central Your Skills and Experience Strong commercial experience building and deploying ML pipelines in production Experience with asynchronous ML inference pipelines Deep understanding of end-to-end ML workflows from research through to deployment Ability to operate with ownership in complex, fast-moving environments Strong communication skills for working with both technical and non-technical stakeholders Experience designing systems within modern cloud environments such as AWS or GCP Proficiency in Python and common ML frameworks such as PyTorch, TensorFlow, or scikit-learn Exposure to ML/MLOps tooling such as SageMaker, MLflow, or TFServing Experience with Spark, Databricks, CI/CD tools, and streaming or orchestration systems like Kafka or Airflow How to Apply If you are interested in this Machine Learning Engineer position, please apply with your CV.
01/04/2026
Contractor
ML Engineer £500-£560 The Company They are a well-established consumer technology business with a mission to create a safe, trusted environment for millions of users. Data, experimentation, and scalable engineering are core to how they operate. Their Trust function is expanding, and they are investing heavily in modern ML infrastructure to support rapid growth. You will join a collaborative environment where ML Engineers, Scientists, Backend Engineers, and MLOps specialists work closely to deliver measurable impact. The Role In this role, you will: Design and implement pipelines for training, evaluating, deploying, and monitoring detection models Productionise detection models in partnership with ML Scientists, improving reliability and latency across asynchronous inference workflows Collaborate with backend and product teams to define integration requirements for trust detection services Extend ML infrastructure with MLOps teams, including reproducible training workflows, CI/CD for model deployment, batch and real-time model serving, feature consistency, and monitoring Uphold strong standards around testing, observability, and operational excellence Contribute to a scaling engineering culture where experimentation and measurable outcomes are central Your Skills and Experience Strong commercial experience building and deploying ML pipelines in production Experience with asynchronous ML inference pipelines Deep understanding of end-to-end ML workflows from research through to deployment Ability to operate with ownership in complex, fast-moving environments Strong communication skills for working with both technical and non-technical stakeholders Experience designing systems within modern cloud environments such as AWS or GCP Proficiency in Python and common ML frameworks such as PyTorch, TensorFlow, or scikit-learn Exposure to ML/MLOps tooling such as SageMaker, MLflow, or TFServing Experience with Spark, Databricks, CI/CD tools, and streaming or orchestration systems like Kafka or Airflow How to Apply If you are interested in this Machine Learning Engineer position, please apply with your CV.
Team - Data Science Working Pattern - Hybrid - 2 days per week in the Vitality London Office. Full time, 37.5 hours per week. We are happy to discuss flexible working! Top 3 skills needed for this role: Expert AI/ML Skills - Strong in both traditional ML and modern LLM/RAG/agentic workflows Production Deployment & MLOps - Comfortable shipping scalable AI systems using APIs, microservices, Docker/Kubernetes, and cloud (GCP ideal) Business Partnering - Able to translate business needs into clear technical requirements and work across teams What this role is all about: At Vitality, data scientists and AI Engineers develop and deploy innovative AI applications spanning the entire value chain of our business, including marketing, sales & retention, underwriting, claims, health and wellness management, customer service, and fraud. The Data Science function is recognised as a core driver of strategic value within the business, with a high-profile and strong support allowing the team to confidently take on and deliver transformational projects.We are seeking highly skilled AI Engineers to join our growing team. You will design, develop, and deploy AI-driven applications leveraging both traditional machine learning and LLM based applications. The role involves building internal and external AI solutions such as Retrieval-Augmented Generation (RAG) systems, chatbots, and voice-based customer service platforms, all deployed on Google Cloud Platform (GCP). You will work closely with data scientists, software engineers, and product teams to deliver robust, scalable, and production-ready AI solutions. Key Actions Stay current with advancements in LLM frameworks, agentic SDKs, and cloud-native AI deployment Work with the business to gather business requirements for new AI applications Design and implement AI applications Deploy AI applications into production environments on a Google Cloud Platform Collaborate with cross-functional teams to integrate AI applications with Enterprise systems Optimise models for performance, scalability, and cost-efficiency What do you need to thrive? Demonstrable experience of working with the business to create a detailed set of project requirements Strong foundation in traditional machine learning (classification, regression, etc.) Hands-on experience with LLM-based applications Experience building RAG systems and agentic workflows that leverage external tools Familiarity with agentic SDKs (ADK, LangChain, LlamaIndex, etc.) Proven track record of deploying AI applications into production environments Strong understanding of API development, microservices, and containerization (Docker, Kubernetes) Knowledge of MLOps best practices Excellent problem-solving skills and ability to work in a fast-paced environment So, what's in it for you? Bonus Schemes - A bonus that regularly rewards you for your performance A pension of up to 12%- We will match your contributions up to 6% of your salary Our award-winning Vitality health insurance - With its own set of rewards and benefits Life Assurance - Four times annual salary These are just some of the many perks that we offer! To view the extensive range of benefits we offer, please visit our careers page. Fantastic Benefits. Exciting rewards. Great career opportunities! If you are successful in your application and join us at Vitality, this is our promise to you, w e will: Help you to be the healthiest you've ever been Create an environment that embraces you as you are and enables you to be your best self Give you flexibility on how, where and when you work Help you advance your career by playing you to your strengths Give you a voice to help our business grow and make Vitality a great place to be Give you the space to try, fail and learn Provide a healthy balance of challenge and support Recognise and reward you with a competitive salary and amazing benefits Be there for you when you need us Provide opportunities for you to be a force for good in society We commit to all these things because we want you to feel that you belong, and are supported to be happy and healthy.About The CompanyWe're incredibly proud to be recognised for the culture we've created - recently being named one of Glassdoor's Best Places to Work 2026 , and in 2024 we were delighted to be awarded Top 10 Places to Work in the Sunday Times Awards. Vitality is a multi-award-winning UK insurance brand, here to make the world a healthier, happier place.We've been a purpose and values-driven business from day 1- long before it became fashionable. Our core purpose is to make people healthier and enhance protect their lives. Vitality pioneered shared-value insurance. We incentivise people to live healthier longer lives - they benefit, our business benefits, and society benefits. We're successful because we attract, develop, and retain the best people - and because we care. Diversity & Inclusion At Vitality, we're committed to diversity and inclusion because it's good for our employees, for our business, and for society. We welcome applications from individuals of all backgrounds, experiences, and perspectives. Vitality's approach to sustainability Vitality is a business that drives positive change. We reward people for making and sustaining healthier choices. But healthy people also need a healthy environment. To learn more please visit our Careers page.
01/04/2026
Full time
Team - Data Science Working Pattern - Hybrid - 2 days per week in the Vitality London Office. Full time, 37.5 hours per week. We are happy to discuss flexible working! Top 3 skills needed for this role: Expert AI/ML Skills - Strong in both traditional ML and modern LLM/RAG/agentic workflows Production Deployment & MLOps - Comfortable shipping scalable AI systems using APIs, microservices, Docker/Kubernetes, and cloud (GCP ideal) Business Partnering - Able to translate business needs into clear technical requirements and work across teams What this role is all about: At Vitality, data scientists and AI Engineers develop and deploy innovative AI applications spanning the entire value chain of our business, including marketing, sales & retention, underwriting, claims, health and wellness management, customer service, and fraud. The Data Science function is recognised as a core driver of strategic value within the business, with a high-profile and strong support allowing the team to confidently take on and deliver transformational projects.We are seeking highly skilled AI Engineers to join our growing team. You will design, develop, and deploy AI-driven applications leveraging both traditional machine learning and LLM based applications. The role involves building internal and external AI solutions such as Retrieval-Augmented Generation (RAG) systems, chatbots, and voice-based customer service platforms, all deployed on Google Cloud Platform (GCP). You will work closely with data scientists, software engineers, and product teams to deliver robust, scalable, and production-ready AI solutions. Key Actions Stay current with advancements in LLM frameworks, agentic SDKs, and cloud-native AI deployment Work with the business to gather business requirements for new AI applications Design and implement AI applications Deploy AI applications into production environments on a Google Cloud Platform Collaborate with cross-functional teams to integrate AI applications with Enterprise systems Optimise models for performance, scalability, and cost-efficiency What do you need to thrive? Demonstrable experience of working with the business to create a detailed set of project requirements Strong foundation in traditional machine learning (classification, regression, etc.) Hands-on experience with LLM-based applications Experience building RAG systems and agentic workflows that leverage external tools Familiarity with agentic SDKs (ADK, LangChain, LlamaIndex, etc.) Proven track record of deploying AI applications into production environments Strong understanding of API development, microservices, and containerization (Docker, Kubernetes) Knowledge of MLOps best practices Excellent problem-solving skills and ability to work in a fast-paced environment So, what's in it for you? Bonus Schemes - A bonus that regularly rewards you for your performance A pension of up to 12%- We will match your contributions up to 6% of your salary Our award-winning Vitality health insurance - With its own set of rewards and benefits Life Assurance - Four times annual salary These are just some of the many perks that we offer! To view the extensive range of benefits we offer, please visit our careers page. Fantastic Benefits. Exciting rewards. Great career opportunities! If you are successful in your application and join us at Vitality, this is our promise to you, w e will: Help you to be the healthiest you've ever been Create an environment that embraces you as you are and enables you to be your best self Give you flexibility on how, where and when you work Help you advance your career by playing you to your strengths Give you a voice to help our business grow and make Vitality a great place to be Give you the space to try, fail and learn Provide a healthy balance of challenge and support Recognise and reward you with a competitive salary and amazing benefits Be there for you when you need us Provide opportunities for you to be a force for good in society We commit to all these things because we want you to feel that you belong, and are supported to be happy and healthy.About The CompanyWe're incredibly proud to be recognised for the culture we've created - recently being named one of Glassdoor's Best Places to Work 2026 , and in 2024 we were delighted to be awarded Top 10 Places to Work in the Sunday Times Awards. Vitality is a multi-award-winning UK insurance brand, here to make the world a healthier, happier place.We've been a purpose and values-driven business from day 1- long before it became fashionable. Our core purpose is to make people healthier and enhance protect their lives. Vitality pioneered shared-value insurance. We incentivise people to live healthier longer lives - they benefit, our business benefits, and society benefits. We're successful because we attract, develop, and retain the best people - and because we care. Diversity & Inclusion At Vitality, we're committed to diversity and inclusion because it's good for our employees, for our business, and for society. We welcome applications from individuals of all backgrounds, experiences, and perspectives. Vitality's approach to sustainability Vitality is a business that drives positive change. We reward people for making and sustaining healthier choices. But healthy people also need a healthy environment. To learn more please visit our Careers page.
Azure Platform Engineer (Azure Foundry IaC Cloud Engineering) Contract: 3-6 months (Inside IR35) Rate: Market Rate Client: Telecommunications Location: Remote (may need occasional UK travel once per quarter to Newbury) We are looking for an experienced Azure Platform Engineer to support the delivery of secure, scalable, and automated cloud platforms across Azure Public Cloud, Hybrid, and Edge environments. This role focuses heavily on Azure Foundry , Infrastructure-as-Code , and Cloud Platform Engineering . Key Responsibilities Engineer secure Azure environments using IaC (Terraform, Bicep). Deliver Azure Landing Zones aligned to CAF & Well-Architected Framework. Azure Foundry Build and scale cloud platforms supporting AI/ML workloads and Azure Foundry services. Implement automation across CI/CD pipelines using Azure DevOps . Support cloud migrations and hybrid/edge deployments. Design cloud-native solutions including AKS and containerized workloads. Embed governance, security, and compliance across platform designs. Required Skills Strong Azure engineering background across IaaS, PaaS, and cloud-native services. Expertise with Terraform , Bicep/ARM , and IaC best practices. Hands-on experience with Azure DevOps (pipelines, repos, release). Knowledge of Azure networking, security, and Entra ID . Experience with Kubernetes / AKS and container architectures. Exposure to Hybrid and Edge solutions. Azure Foundry & AI (Highly Desirable) Experience with Azure Foundry or AI platform services. Understanding of enabling AI/ML workloads on Azure. Ability to integrate AI services into cloud platforms via IaC and DevOps. Familiarity with MLOps concepts and AI governance.
31/03/2026
Contractor
Azure Platform Engineer (Azure Foundry IaC Cloud Engineering) Contract: 3-6 months (Inside IR35) Rate: Market Rate Client: Telecommunications Location: Remote (may need occasional UK travel once per quarter to Newbury) We are looking for an experienced Azure Platform Engineer to support the delivery of secure, scalable, and automated cloud platforms across Azure Public Cloud, Hybrid, and Edge environments. This role focuses heavily on Azure Foundry , Infrastructure-as-Code , and Cloud Platform Engineering . Key Responsibilities Engineer secure Azure environments using IaC (Terraform, Bicep). Deliver Azure Landing Zones aligned to CAF & Well-Architected Framework. Azure Foundry Build and scale cloud platforms supporting AI/ML workloads and Azure Foundry services. Implement automation across CI/CD pipelines using Azure DevOps . Support cloud migrations and hybrid/edge deployments. Design cloud-native solutions including AKS and containerized workloads. Embed governance, security, and compliance across platform designs. Required Skills Strong Azure engineering background across IaaS, PaaS, and cloud-native services. Expertise with Terraform , Bicep/ARM , and IaC best practices. Hands-on experience with Azure DevOps (pipelines, repos, release). Knowledge of Azure networking, security, and Entra ID . Experience with Kubernetes / AKS and container architectures. Exposure to Hybrid and Edge solutions. Azure Foundry & AI (Highly Desirable) Experience with Azure Foundry or AI platform services. Understanding of enabling AI/ML workloads on Azure. Ability to integrate AI services into cloud platforms via IaC and DevOps. Familiarity with MLOps concepts and AI governance.
We are seeking an experienced AI Architect to join a global consulting team. This role is central to shaping enterprise-scale AI transformations, combining deep technical expertise with strategic client engagement. As a Gen AI Architect, you will: Lead the design and delivery of AI and cloud-native architectures, including Generative AI, NLP, and LLM solutions. Retrieval-Augmented Generation (RAG) and CAG (Cache Augmented) Architecture: Defining architectural patterns for end-to-end pipelines Act as a trusted advisor to senior stakeholders, guiding AI roadmaps and strategy. Translate complex business needs into scalable AI-driven solutions across public cloud, edge, and hybrid environments. Drive thought leadership through client workshops, industry forums, and technical advisory. Ensure AI solutions meet governance, ethics, and responsible AI standards. Collaborate with internal teams and global partners to deliver world-class AI platforms. Key Skills & Experience: 10+ years of technical leadership (with a strong background in Software Engineering / Enterprise scale architecture) Knowledge of GenAI operations (ideally, experience governing AI models in production environments) Expertise across cloud platforms (AWS, Azure, GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If you have these skills and would like to find out more, please apply now
31/03/2026
Full time
We are seeking an experienced AI Architect to join a global consulting team. This role is central to shaping enterprise-scale AI transformations, combining deep technical expertise with strategic client engagement. As a Gen AI Architect, you will: Lead the design and delivery of AI and cloud-native architectures, including Generative AI, NLP, and LLM solutions. Retrieval-Augmented Generation (RAG) and CAG (Cache Augmented) Architecture: Defining architectural patterns for end-to-end pipelines Act as a trusted advisor to senior stakeholders, guiding AI roadmaps and strategy. Translate complex business needs into scalable AI-driven solutions across public cloud, edge, and hybrid environments. Drive thought leadership through client workshops, industry forums, and technical advisory. Ensure AI solutions meet governance, ethics, and responsible AI standards. Collaborate with internal teams and global partners to deliver world-class AI platforms. Key Skills & Experience: 10+ years of technical leadership (with a strong background in Software Engineering / Enterprise scale architecture) Knowledge of GenAI operations (ideally, experience governing AI models in production environments) Expertise across cloud platforms (AWS, Azure, GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If you have these skills and would like to find out more, please apply now
This is a fantastic opportunity to work as an MLOps Engineer on a remote basis, outside IR35, for a major pharmaceutical company. The key skills required for this MLOps Engineer position are: MLOps Image data AWS PyTorch, TensorFlow, JAX If you do have the relevant experience for this long term remote contract MLOps Engineer role, outside IR35, please do apply.
31/03/2026
Contractor
This is a fantastic opportunity to work as an MLOps Engineer on a remote basis, outside IR35, for a major pharmaceutical company. The key skills required for this MLOps Engineer position are: MLOps Image data AWS PyTorch, TensorFlow, JAX If you do have the relevant experience for this long term remote contract MLOps Engineer role, outside IR35, please do apply.
AI Architect Financial Services London Hybrid At Datatech Analytics, we're delighted to partner with a global consulting organisation expanding its AI and Data capability within Financial Services. The firm works with major banks, insurers and capital markets institutions to design and deploy enterprise AI platforms, helping organisations transform how data and AI drive decision making across the business. As demand for AI transformation programmes continues to grow, the business is looking to hire an AI Architect to help shape and deliver complex AI platforms for large financial institutions. The role You will design and architect enterprise AI platforms, translating complex business challenges into scalable AI and data solutions. Working closely with engineering teams and senior stakeholders, you'll help organisations move from experimentation with AI to production-ready AI systems embedded within core business platforms. What you'll be doing Defining enterprise AI architecture strategies for financial services clients. Designing scalable AI platforms and ML infrastructure integrated with enterprise data systems. Architecting end-to-end AI pipelines , from data ingestion through to model deployment. Leading engineering teams across AI, machine learning and data engineering. Engaging senior stakeholders to shape AI transformation programmes and technical strategy. Technology environment Typical platforms and technologies include: Cloud platforms such as AWS, Azure or Google Cloud Data platforms including Databricks, Snowflake or BigQuery Python and modern ML frameworks Generative AI, LLM integration and RAG pipelines MLOps tooling and modern ML lifecycle management. The profile Experience designing enterprise AI or data platforms in complex technology environments. A background delivering large-scale transformation programmes, often within consulting or advisory environments. Strong technical leadership combined with the ability to engage senior stakeholders across business and technology teams. Experience working within Financial Services environments is highly valued. If you'd like to learn more about the opportunity, feel free to reach out for a confidential conversation.APPLY NOW Datatech Analytics
31/03/2026
Full time
AI Architect Financial Services London Hybrid At Datatech Analytics, we're delighted to partner with a global consulting organisation expanding its AI and Data capability within Financial Services. The firm works with major banks, insurers and capital markets institutions to design and deploy enterprise AI platforms, helping organisations transform how data and AI drive decision making across the business. As demand for AI transformation programmes continues to grow, the business is looking to hire an AI Architect to help shape and deliver complex AI platforms for large financial institutions. The role You will design and architect enterprise AI platforms, translating complex business challenges into scalable AI and data solutions. Working closely with engineering teams and senior stakeholders, you'll help organisations move from experimentation with AI to production-ready AI systems embedded within core business platforms. What you'll be doing Defining enterprise AI architecture strategies for financial services clients. Designing scalable AI platforms and ML infrastructure integrated with enterprise data systems. Architecting end-to-end AI pipelines , from data ingestion through to model deployment. Leading engineering teams across AI, machine learning and data engineering. Engaging senior stakeholders to shape AI transformation programmes and technical strategy. Technology environment Typical platforms and technologies include: Cloud platforms such as AWS, Azure or Google Cloud Data platforms including Databricks, Snowflake or BigQuery Python and modern ML frameworks Generative AI, LLM integration and RAG pipelines MLOps tooling and modern ML lifecycle management. The profile Experience designing enterprise AI or data platforms in complex technology environments. A background delivering large-scale transformation programmes, often within consulting or advisory environments. Strong technical leadership combined with the ability to engage senior stakeholders across business and technology teams. Experience working within Financial Services environments is highly valued. If you'd like to learn more about the opportunity, feel free to reach out for a confidential conversation.APPLY NOW Datatech Analytics
Location: Bristol (20% onsite) Duration: 6 month contract Rate: 78ph LTD (Outside IR35) Role details: Our client, a leader in the defence and security sector, is seeking a Senior Machine Learning Engineer to join their team on a contract basis. This role involves developing and deploying advanced machine learning models essential for secure, high-integrity systems and services across critical defence, government, and public sector programmes. Key Responsibilities: Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics Own the ML lifecycle from data preparation through to training, evaluation, and deployment Implement and maintain MLOps workflows for continuous integration and delivery of ML models Collaborate with Data Engineers and DevOps teams to ensure production readiness and scalability Contribute to architecture decisions for ML pipelines and data flows Apply secure coding and configuration practices in line with compliance standards Mentor junior engineers and share best practices across the team Support innovation by researching emerging ML techniques and tools Job Requirements: Proven experience developing and deploying machine learning models in production environments Experience with the OpenCV framework and object detection models, including YOLO, RCNN, and Vision models Proficiency in optical flow and object tracking for video analysis Solid knowledge of Optical Character Recognition (OCR) models and fine-tuning with custom datasets Understanding of accuracy measurement metrics like Character Error Rate (CER) and Word Error Rate (WER) Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch) Understanding of ML architectures, hyperparameter tuning, and performance optimisation Experience with MLOps tools and CI/CD pipelines Familiarity with data engineering concepts (ETL, data pipelines, SQL) Ability to analyse complex data and communicate insights effectively Strong problem-solving skills and attention to detail Excellent collaboration and stakeholder engagement skills Core Areas (Must Have): ML Development Expertise: Hands-on experience building and deploying ML models Lifecycle Ownership: Ability to manage ML workflows from design to production Tool Proficiency: Skilled in Python, ML frameworks, and MLOps tooling Data Engineering Awareness: Understanding of data pipelines, warehousing, and integration Governance & Compliance: Familiarity with secure coding and quality assurance standards Collaboration & Mentoring: Ability to work across teams and support junior engineers Continuous Improvement: Commitment to learning and applying emerging ML techniques Desirable Skills: Experience with cloud platforms (AWS) and containerisation (such as Docker, Podman, Kubernetes) Experience working in secure or regulated environments Exposure to big data technologies (Spark, Hadoop) and Apache tools Familiarity with Agile and DevOps practices Industry certifications (e.g., TensorFlow Developer, AWS Machine Learning Specialty) Knowledge of NLP, computer vision, and deep learning architectures STEM degree or equivalent experience in AI, Data Science, or related fields If you are ready to take ownership of machine learning solutions that underpin secure, high-integrity systems and services, and lead in solving customer problems in an agile, innovative, and team-centric manner, we would love to hear from you. Apply now to join our client's Cyber & Security Solutions Division team in Bristol.
31/03/2026
Contractor
Location: Bristol (20% onsite) Duration: 6 month contract Rate: 78ph LTD (Outside IR35) Role details: Our client, a leader in the defence and security sector, is seeking a Senior Machine Learning Engineer to join their team on a contract basis. This role involves developing and deploying advanced machine learning models essential for secure, high-integrity systems and services across critical defence, government, and public sector programmes. Key Responsibilities: Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics Own the ML lifecycle from data preparation through to training, evaluation, and deployment Implement and maintain MLOps workflows for continuous integration and delivery of ML models Collaborate with Data Engineers and DevOps teams to ensure production readiness and scalability Contribute to architecture decisions for ML pipelines and data flows Apply secure coding and configuration practices in line with compliance standards Mentor junior engineers and share best practices across the team Support innovation by researching emerging ML techniques and tools Job Requirements: Proven experience developing and deploying machine learning models in production environments Experience with the OpenCV framework and object detection models, including YOLO, RCNN, and Vision models Proficiency in optical flow and object tracking for video analysis Solid knowledge of Optical Character Recognition (OCR) models and fine-tuning with custom datasets Understanding of accuracy measurement metrics like Character Error Rate (CER) and Word Error Rate (WER) Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch) Understanding of ML architectures, hyperparameter tuning, and performance optimisation Experience with MLOps tools and CI/CD pipelines Familiarity with data engineering concepts (ETL, data pipelines, SQL) Ability to analyse complex data and communicate insights effectively Strong problem-solving skills and attention to detail Excellent collaboration and stakeholder engagement skills Core Areas (Must Have): ML Development Expertise: Hands-on experience building and deploying ML models Lifecycle Ownership: Ability to manage ML workflows from design to production Tool Proficiency: Skilled in Python, ML frameworks, and MLOps tooling Data Engineering Awareness: Understanding of data pipelines, warehousing, and integration Governance & Compliance: Familiarity with secure coding and quality assurance standards Collaboration & Mentoring: Ability to work across teams and support junior engineers Continuous Improvement: Commitment to learning and applying emerging ML techniques Desirable Skills: Experience with cloud platforms (AWS) and containerisation (such as Docker, Podman, Kubernetes) Experience working in secure or regulated environments Exposure to big data technologies (Spark, Hadoop) and Apache tools Familiarity with Agile and DevOps practices Industry certifications (e.g., TensorFlow Developer, AWS Machine Learning Specialty) Knowledge of NLP, computer vision, and deep learning architectures STEM degree or equivalent experience in AI, Data Science, or related fields If you are ready to take ownership of machine learning solutions that underpin secure, high-integrity systems and services, and lead in solving customer problems in an agile, innovative, and team-centric manner, we would love to hear from you. Apply now to join our client's Cyber & Security Solutions Division team in Bristol.
Senior Machine Learning Engineer 6 month contract Based in Bristol Offering circa 75ph Outside IR35 Do you have experience designing, building, and optimising ML models? Do you have experience in Python and ML frameworks? Do you want to work with an industry-leading company? If your answer to these is yes, then this could be the role for you! As the Senior Machine Learning Engineer, you will be working alongside a market-leading Defence and Aerospace company who are constantly growing and developing. They are always looking to bring on new talents such as yourself and further develop your skills to enable you to grow within the company and industry. Do you the nature of the work you will be invoved in, you will be required to go through MOD SC clearance. You will be involved in: Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics Own the ML lifecycle from data preparation through training, evaluation, and deployment Implement and maintain MLOps workflows for continuous integration and delivery of ML models Collaborate with Data Engineers and DevOps teams to ensure production readiness and scalability Contribute to architecture decisions for ML pipelines and data flows Apply secure coding and configuration practices in line with compliance standards Mentor junior engineers and share best practices across the team Support innovation by researching emerging ML techniques and tools Your skillset may include: ML Development Expertise: Hands-on experience building and deploying ML models Lifecycle Ownership: Ability to manage ML workflows from design to production Tool Proficiency: Skilled in Python, ML frameworks, and MLOps tooling Data Engineering Awareness: Understanding of data pipelines, warehousing, and integration Governance & Compliance: Familiarity with secure coding and quality assurance standards Collaboration & Mentoring: Ability to work across teams and support junior engineers Continuous Improvement: Commitment to learning and applying emerging ML techniques If this all sounds like something you will be interested in then simply apply and we can discuss the opportunity further! Senior Machine Learning Engineer 6 month contract Based in Bristol Offering circa 75ph Outside IR35 Disclaimer: This vacancy is being advertised by either Advanced Resource Managers Limited, Advanced Resource Managers IT Limited or Advanced Resource Managers Engineering Limited ("ARM"). ARM is a specialist talent acquisition and management consultancy. We provide technical contingency recruitment and a portfolio of more complex resource solutions. Our specialist recruitment divisions cover the entire technical arena, including some of the most economically and strategically important industries in the UK and the world today. We will never send your CV without your permission. Where the role is marked as Outside IR35 in the advertisement this is subject to receipt of a final Status Determination Statement from the end Client and may be subject to change.
31/03/2026
Contractor
Senior Machine Learning Engineer 6 month contract Based in Bristol Offering circa 75ph Outside IR35 Do you have experience designing, building, and optimising ML models? Do you have experience in Python and ML frameworks? Do you want to work with an industry-leading company? If your answer to these is yes, then this could be the role for you! As the Senior Machine Learning Engineer, you will be working alongside a market-leading Defence and Aerospace company who are constantly growing and developing. They are always looking to bring on new talents such as yourself and further develop your skills to enable you to grow within the company and industry. Do you the nature of the work you will be invoved in, you will be required to go through MOD SC clearance. You will be involved in: Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics Own the ML lifecycle from data preparation through training, evaluation, and deployment Implement and maintain MLOps workflows for continuous integration and delivery of ML models Collaborate with Data Engineers and DevOps teams to ensure production readiness and scalability Contribute to architecture decisions for ML pipelines and data flows Apply secure coding and configuration practices in line with compliance standards Mentor junior engineers and share best practices across the team Support innovation by researching emerging ML techniques and tools Your skillset may include: ML Development Expertise: Hands-on experience building and deploying ML models Lifecycle Ownership: Ability to manage ML workflows from design to production Tool Proficiency: Skilled in Python, ML frameworks, and MLOps tooling Data Engineering Awareness: Understanding of data pipelines, warehousing, and integration Governance & Compliance: Familiarity with secure coding and quality assurance standards Collaboration & Mentoring: Ability to work across teams and support junior engineers Continuous Improvement: Commitment to learning and applying emerging ML techniques If this all sounds like something you will be interested in then simply apply and we can discuss the opportunity further! Senior Machine Learning Engineer 6 month contract Based in Bristol Offering circa 75ph Outside IR35 Disclaimer: This vacancy is being advertised by either Advanced Resource Managers Limited, Advanced Resource Managers IT Limited or Advanced Resource Managers Engineering Limited ("ARM"). ARM is a specialist talent acquisition and management consultancy. We provide technical contingency recruitment and a portfolio of more complex resource solutions. Our specialist recruitment divisions cover the entire technical arena, including some of the most economically and strategically important industries in the UK and the world today. We will never send your CV without your permission. Where the role is marked as Outside IR35 in the advertisement this is subject to receipt of a final Status Determination Statement from the end Client and may be subject to change.
Our client is building the most advanced AI platform in their market. They help their clients serve customers with unmatched speed and accuracy. They ve invested heavily into building the ML stack, partnered with leading universities, and trained models on millions of expert-tagged images. Now, they re scaling globally and need a world-class Lead Data Scientist to help push the boundaries of computer vision, video analysis, and multimodal LLMs while solving real-world challenges. Role Overview They are looking for an experienced Lead Data Scientist to spearhead machine-learning initiatives, with particular focus on computer vision, large language models, and production ready ML pipelines in Azure. You will act as the technical lead for the team, setting direction, guiding best practices, and ensuring the successful delivery of high-impact AI solutions. Key Responsibilities Develop, train, and deploy computer vision models (object detection, image classification, segmentation, multi-modal learning) Fine-tune, evaluate, and productionise multi-modal LLMs for business applications. Drive experimentation and prototyping of advanced ML/AI techniques Provide technical direction, mentoring, and hands-on guidance to the data science team. Work with engineering, product, and business stakeholders to align ML strategy with business goals. Architect and productionise end-to-end ML pipelines on Azure, while ensuring scalability, reproducibility, and monitoring of deployed models. Requirements 6+ years in data science / ML, with at least 2 years in a technical lead role. Deep experience in training and deploying computer vision models into production Proven track record with LLM fine-tuning, prompt engineering and productionisation Deep experience in MLOps on Azure, including CI/CD, monitoring and scaling pipelines. Strong coding skills in Python, with frameworks such as PyTorch, FastAPI and Azure CLI. ALL APPLICANTS MUST BE FREE TO WORK IN THE UK Exposed Solutions is acting as an employment agency to this client. Please note that no terminology in this advert is intended to discriminate on any grounds, and we confirm that we will gladly accept applications from any person for this role.
31/03/2026
Full time
Our client is building the most advanced AI platform in their market. They help their clients serve customers with unmatched speed and accuracy. They ve invested heavily into building the ML stack, partnered with leading universities, and trained models on millions of expert-tagged images. Now, they re scaling globally and need a world-class Lead Data Scientist to help push the boundaries of computer vision, video analysis, and multimodal LLMs while solving real-world challenges. Role Overview They are looking for an experienced Lead Data Scientist to spearhead machine-learning initiatives, with particular focus on computer vision, large language models, and production ready ML pipelines in Azure. You will act as the technical lead for the team, setting direction, guiding best practices, and ensuring the successful delivery of high-impact AI solutions. Key Responsibilities Develop, train, and deploy computer vision models (object detection, image classification, segmentation, multi-modal learning) Fine-tune, evaluate, and productionise multi-modal LLMs for business applications. Drive experimentation and prototyping of advanced ML/AI techniques Provide technical direction, mentoring, and hands-on guidance to the data science team. Work with engineering, product, and business stakeholders to align ML strategy with business goals. Architect and productionise end-to-end ML pipelines on Azure, while ensuring scalability, reproducibility, and monitoring of deployed models. Requirements 6+ years in data science / ML, with at least 2 years in a technical lead role. Deep experience in training and deploying computer vision models into production Proven track record with LLM fine-tuning, prompt engineering and productionisation Deep experience in MLOps on Azure, including CI/CD, monitoring and scaling pipelines. Strong coding skills in Python, with frameworks such as PyTorch, FastAPI and Azure CLI. ALL APPLICANTS MUST BE FREE TO WORK IN THE UK Exposed Solutions is acting as an employment agency to this client. Please note that no terminology in this advert is intended to discriminate on any grounds, and we confirm that we will gladly accept applications from any person for this role.
Job Title: Lead Machine Learning Engineer (SageMaker, MLOps, Explainability) Job Description We are seeking an experienced Lead Machine Learning Engineer to design, build, and productionise machine learning models for our innovative matching platform. You will work across the entire ML lifecycle, from feature engineering to deployment automation, ensuring the optimisation and explainability of inference processes. Collaborating closely with data scientists and product teams, your role will focus on enhancing MLOps practices, ensuring high standards of security, performance, and compliance. Responsibilities Build and maintain scalable feature pipelines within data lakehouse architectures. Develop fallback feature flows and implement robust data quality checks. Develop ranking, scoring, and entity-similarity models for the matching platform. Use modern ML model frameworks such as PyTorch, TensorFlow, or XGBoost. Apply SHAP or similar techniques to generate interpretable model explanations. Build and maintain training, processing, and inference pipelines using AWS SageMaker. Deploy and optimise low-latency, real-time inference endpoints. Implement feature drift and concept drift monitoring. Apply procedures for data handling, encryption, PII minimisation, and auditability. Conduct validation of models using golden datasets and baseline tests. Essential Skills Strong experience delivering production-grade ML systems. Proficiency with AWS SageMaker, including training jobs and Model Registry. Excellent skills with ML models like PyTorch, TensorFlow, or XGBoost. Hands-on experience with model explainability tools such as SHAP. Understanding of low-latency, real-time inference patterns. experience in drift detection, monitoring, and telemetry. Working knowledge of ML governance and secure ML practices. Strong understanding of MLOps, CI/CD, and automation for ML workflows. Additional Skills & Qualifications experience with feature stores or Lakehouse data architectures. Previous experience with ranking, matching, or similarity models. Familiarity with cross-account AWS IAM patterns. Bachelor's degree in a STEM subject such as mathematics, physics, engineering, or computer science. Why Work Here? Join a forward-thinking company focused on innovation and excellence in machine learning. We provide a collaborative environment where your contributions directly impact the development of cutting-edge technology. Enjoy opportunities for professional growth and be part of a team dedicated to pioneering advancements in AI/ML. Work Environment Work in a dynamic and collaborative environment leveraging state-of-the-art technologies. You will have access to modern tools and resources, including AWS SageMaker and various ML frameworks. Our flexible work culture promotes work-life balance and encourages continuous learning and development. Location London, UK Trading as TEKsystems. Allegis Group Limited, Maxis 2, Western Road, Bracknell, RG12 1RT, United Kingdom. No. (phone number removed). Allegis Group Limited operates as an Employment Business and Employment Agency as set out in the Conduct of Employment Agencies and Employment Businesses Regulations 2003. TEKsystems is a company within the Allegis Group network of companies (collectively referred to as "Allegis Group"). Aerotek, Aston Carter, EASi, Talentis Solutions, TEKsystems, Stamford Consultants and The Stamford Group are Allegis Group brands. If you apply, your personal data will be processed as described in the Allegis Group Online Privacy Notice available at (url removed)> To access our Online Privacy Notice, which explains what information we may collect, use, share, and store about you, and describes your rights and choices about this, please go to (url removed)> We are part of a global network of companies and as a result, the personal data you provide will be shared within Allegis Group and transferred and processed outside the UK, Switzerland and European Economic Area subject to the protections described in the Allegis Group Online Privacy Notice. We store personal data in the UK, EEA, Switzerland and the USA. If you would like to exercise your privacy rights, please visit the "Contacting Us" section of our Online Privacy Notice at (url removed)/en-gb/privacy-notices for details on how to contact us. To protect your privacy and security, we may take steps to verify your identity, such as a password and user ID if there is an account associated with your request, or identifying information such as your address or date of birth, before proceeding with your request. If you are resident in the UK, EEA or Switzerland, we will process any access request you make in accordance with our commitments under the UK Data Protection Act, EU-U.S. Privacy Shield or the Swiss-U.S. Privacy Shield.
26/03/2026
Seasonal
Job Title: Lead Machine Learning Engineer (SageMaker, MLOps, Explainability) Job Description We are seeking an experienced Lead Machine Learning Engineer to design, build, and productionise machine learning models for our innovative matching platform. You will work across the entire ML lifecycle, from feature engineering to deployment automation, ensuring the optimisation and explainability of inference processes. Collaborating closely with data scientists and product teams, your role will focus on enhancing MLOps practices, ensuring high standards of security, performance, and compliance. Responsibilities Build and maintain scalable feature pipelines within data lakehouse architectures. Develop fallback feature flows and implement robust data quality checks. Develop ranking, scoring, and entity-similarity models for the matching platform. Use modern ML model frameworks such as PyTorch, TensorFlow, or XGBoost. Apply SHAP or similar techniques to generate interpretable model explanations. Build and maintain training, processing, and inference pipelines using AWS SageMaker. Deploy and optimise low-latency, real-time inference endpoints. Implement feature drift and concept drift monitoring. Apply procedures for data handling, encryption, PII minimisation, and auditability. Conduct validation of models using golden datasets and baseline tests. Essential Skills Strong experience delivering production-grade ML systems. Proficiency with AWS SageMaker, including training jobs and Model Registry. Excellent skills with ML models like PyTorch, TensorFlow, or XGBoost. Hands-on experience with model explainability tools such as SHAP. Understanding of low-latency, real-time inference patterns. experience in drift detection, monitoring, and telemetry. Working knowledge of ML governance and secure ML practices. Strong understanding of MLOps, CI/CD, and automation for ML workflows. Additional Skills & Qualifications experience with feature stores or Lakehouse data architectures. Previous experience with ranking, matching, or similarity models. Familiarity with cross-account AWS IAM patterns. Bachelor's degree in a STEM subject such as mathematics, physics, engineering, or computer science. Why Work Here? Join a forward-thinking company focused on innovation and excellence in machine learning. We provide a collaborative environment where your contributions directly impact the development of cutting-edge technology. Enjoy opportunities for professional growth and be part of a team dedicated to pioneering advancements in AI/ML. Work Environment Work in a dynamic and collaborative environment leveraging state-of-the-art technologies. You will have access to modern tools and resources, including AWS SageMaker and various ML frameworks. Our flexible work culture promotes work-life balance and encourages continuous learning and development. Location London, UK Trading as TEKsystems. Allegis Group Limited, Maxis 2, Western Road, Bracknell, RG12 1RT, United Kingdom. No. (phone number removed). Allegis Group Limited operates as an Employment Business and Employment Agency as set out in the Conduct of Employment Agencies and Employment Businesses Regulations 2003. TEKsystems is a company within the Allegis Group network of companies (collectively referred to as "Allegis Group"). Aerotek, Aston Carter, EASi, Talentis Solutions, TEKsystems, Stamford Consultants and The Stamford Group are Allegis Group brands. If you apply, your personal data will be processed as described in the Allegis Group Online Privacy Notice available at (url removed)> To access our Online Privacy Notice, which explains what information we may collect, use, share, and store about you, and describes your rights and choices about this, please go to (url removed)> We are part of a global network of companies and as a result, the personal data you provide will be shared within Allegis Group and transferred and processed outside the UK, Switzerland and European Economic Area subject to the protections described in the Allegis Group Online Privacy Notice. We store personal data in the UK, EEA, Switzerland and the USA. If you would like to exercise your privacy rights, please visit the "Contacting Us" section of our Online Privacy Notice at (url removed)/en-gb/privacy-notices for details on how to contact us. To protect your privacy and security, we may take steps to verify your identity, such as a password and user ID if there is an account associated with your request, or identifying information such as your address or date of birth, before proceeding with your request. If you are resident in the UK, EEA or Switzerland, we will process any access request you make in accordance with our commitments under the UK Data Protection Act, EU-U.S. Privacy Shield or the Swiss-U.S. Privacy Shield.
Data Architect - 70-90K base (DOE) - West London (hybrid) We are recruiting a Data Architect for one of our clients based in West London on a permanent basis. The Data Architect is responsible for leading the definition, standardization, and governance of data architecture across platforms and products. This role balances technical leadership, data architecture, and collaboration with engineering, product, and security teams to ensure scalable, reliable, and secure systems. Key responsibilities: Enforce data architectural guidelines and consistency across development teams and services Support established Data Governance and Data Quality frameworks, including tooling, policy enforcement, and stewardship models Ensure robust metadata management, lineage tracking, and data cataloguing using business glossaries and modern catalog tools Review and approve data architecture for major features, platforms, and technical initiatives Collaborate with technical leads and DevOps on system scalability, performance, and reliability Ensure data platforms are AI/ML-ready, with scalable infrastructure and clean, well-structured data pipelines Collaborate with data science and analytics teams to enable model deployment, automation, and MLOps best practices Promote innovation in generative AI, predictive analytics, and real-time decision support Align data architecture with security, compliance, and data governance requirements Lead the evolution of technical architecture documentation, models, and decision records Conduct architecture and design reviews with cross-functional teams Guide teams in the adoption of best practices in API design, modularity, cloud-native patterns, and event-driven systems Recommend data management best practices, covering data flows, architecture patterns, retention, archival, and purging strategies Coach and mentor engineers on data design, refactoring, and architectural reasoning Essential skills and experience: Proven experience designing and scaling enterprise-grade cloud data platforms (AWS preferred) Deep experience with AWS, Databricks, Power Platform, and Redshift (Snowflake a plus) Proficiency in AWS Glue, Qlik Talend, DBT, Airflow, and modern data integration tools. Excellent knowledge of Python, SQL, PowerQuery (M), and preferably Scala or PySpark Working knowledge with enterprise architecture frameworks (e.g., TOGAF), MLOps, and BI tools like Power BI and QuickSight Experience of generative AI platforms (e.g., Amazon Bedrock, Anthropic) Familiarity with infrastructure as code (Terraform), CI/CD practices (Jenkins, GitHub Actions), and observability (Grafana, Kibana) Proficiency in scripting and automation using Bash, Groovy, or equivalent Ability to balance long-term architectural vision with immediate delivery constraints Damia Group Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this permanent job, you accept our Data Protection Policy which can be found on our website. Please note that no terminology in this advert is intended to discriminate on the grounds of a person's gender, marital status, race, religion, colour, age, disability or sexual orientation. Every candidate will be assessed only in accordance with their merits, qualifications and ability to perform the duties of the job. Damia Group is acting as an Employment Business in relation to this vacancy and in accordance to Conduct Regulations 2003. The advertised salary range is dependent on experience and the required qualifications. Damia Group Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept our Data Protection Policy which can be found on our website. Please note that no terminology in this advert is intended to discriminate on the grounds of a person's gender, marital status, race, religion, colour, age, disability or sexual orientation. Every candidate will be assessed only in accordance with their merits, qualifications and ability to perform the duties of the job. Damia Group is acting as an Employment Business in relation to this vacancy and in accordance to Conduct Regulations 2003.
26/03/2026
Full time
Data Architect - 70-90K base (DOE) - West London (hybrid) We are recruiting a Data Architect for one of our clients based in West London on a permanent basis. The Data Architect is responsible for leading the definition, standardization, and governance of data architecture across platforms and products. This role balances technical leadership, data architecture, and collaboration with engineering, product, and security teams to ensure scalable, reliable, and secure systems. Key responsibilities: Enforce data architectural guidelines and consistency across development teams and services Support established Data Governance and Data Quality frameworks, including tooling, policy enforcement, and stewardship models Ensure robust metadata management, lineage tracking, and data cataloguing using business glossaries and modern catalog tools Review and approve data architecture for major features, platforms, and technical initiatives Collaborate with technical leads and DevOps on system scalability, performance, and reliability Ensure data platforms are AI/ML-ready, with scalable infrastructure and clean, well-structured data pipelines Collaborate with data science and analytics teams to enable model deployment, automation, and MLOps best practices Promote innovation in generative AI, predictive analytics, and real-time decision support Align data architecture with security, compliance, and data governance requirements Lead the evolution of technical architecture documentation, models, and decision records Conduct architecture and design reviews with cross-functional teams Guide teams in the adoption of best practices in API design, modularity, cloud-native patterns, and event-driven systems Recommend data management best practices, covering data flows, architecture patterns, retention, archival, and purging strategies Coach and mentor engineers on data design, refactoring, and architectural reasoning Essential skills and experience: Proven experience designing and scaling enterprise-grade cloud data platforms (AWS preferred) Deep experience with AWS, Databricks, Power Platform, and Redshift (Snowflake a plus) Proficiency in AWS Glue, Qlik Talend, DBT, Airflow, and modern data integration tools. Excellent knowledge of Python, SQL, PowerQuery (M), and preferably Scala or PySpark Working knowledge with enterprise architecture frameworks (e.g., TOGAF), MLOps, and BI tools like Power BI and QuickSight Experience of generative AI platforms (e.g., Amazon Bedrock, Anthropic) Familiarity with infrastructure as code (Terraform), CI/CD practices (Jenkins, GitHub Actions), and observability (Grafana, Kibana) Proficiency in scripting and automation using Bash, Groovy, or equivalent Ability to balance long-term architectural vision with immediate delivery constraints Damia Group Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this permanent job, you accept our Data Protection Policy which can be found on our website. Please note that no terminology in this advert is intended to discriminate on the grounds of a person's gender, marital status, race, religion, colour, age, disability or sexual orientation. Every candidate will be assessed only in accordance with their merits, qualifications and ability to perform the duties of the job. Damia Group is acting as an Employment Business in relation to this vacancy and in accordance to Conduct Regulations 2003. The advertised salary range is dependent on experience and the required qualifications. Damia Group Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept our Data Protection Policy which can be found on our website. Please note that no terminology in this advert is intended to discriminate on the grounds of a person's gender, marital status, race, religion, colour, age, disability or sexual orientation. Every candidate will be assessed only in accordance with their merits, qualifications and ability to perform the duties of the job. Damia Group is acting as an Employment Business in relation to this vacancy and in accordance to Conduct Regulations 2003.
Global Leader in software supply chain for DevOps, DevSecOps, and MLOps is seeking a pre-sales focused Solutions Architect to work closely with strategic customers and prospects. This role is ideal for someone who thrives at the intersection of technology and business, and who enjoys driving impactful conversations with technical and executive stakeholders. This is a hybrid role based out of London, with three days per week in the office. Excellent + OTE + Bens + Stock Key skills for the Solutions Architect - DevOps Significant experience in technical pre-sales, solutions architecture, or similar roles Strong relationship-building skills with both technical users and senior stakeholders in enterprise environments Practical knowledge and hands-on experience with Docker, Kubernetes, CI/CD pipelines, Git workflows, and build tools Familiarity with application security tools such as SCA, SAST, SBOM management, and container security Ability to build and manage modern software pipelines using diverse DevOps tooling Solid hands-on experience with major cloud platforms (AWS, Azure, GCP) - mandatory Background in software development is a significant advantage K ey responsibilities for the Solutions Architect DevOps - include Engage with customers to ensure their success in their DevOps and DevSecOps journey leveraging the software supply chain Platform Support Sales motion and significantly contribute to the customer journey to build technical wins and championship Train our customers, prospects and community about product offering and solutions Represent the company in events and conferences Influence the features and roadmap of products based on customer needs Stay current with the latest technology trends related to the DevOps and DevSecOps landscape Join a company trusted by thousands of enterprise customers software engineering teams to deliver secure continuous updates, and is used by the majority of the Fortune 100, and help shape the future of secure and efficient software delivery. Opus Resourcing acts as an employment agency with respect to permanent employment. Skills: CI/CD, AZURE, GIT, DEVOPS, DOCKER, KUBERNETES, AWS,presales,Security,cloud platforms,Application Security,SAST,Sales Engineering,Technical Sales Consulting,Pre-Sales Technical Consulting
06/10/2025
Full time
Global Leader in software supply chain for DevOps, DevSecOps, and MLOps is seeking a pre-sales focused Solutions Architect to work closely with strategic customers and prospects. This role is ideal for someone who thrives at the intersection of technology and business, and who enjoys driving impactful conversations with technical and executive stakeholders. This is a hybrid role based out of London, with three days per week in the office. Excellent + OTE + Bens + Stock Key skills for the Solutions Architect - DevOps Significant experience in technical pre-sales, solutions architecture, or similar roles Strong relationship-building skills with both technical users and senior stakeholders in enterprise environments Practical knowledge and hands-on experience with Docker, Kubernetes, CI/CD pipelines, Git workflows, and build tools Familiarity with application security tools such as SCA, SAST, SBOM management, and container security Ability to build and manage modern software pipelines using diverse DevOps tooling Solid hands-on experience with major cloud platforms (AWS, Azure, GCP) - mandatory Background in software development is a significant advantage K ey responsibilities for the Solutions Architect DevOps - include Engage with customers to ensure their success in their DevOps and DevSecOps journey leveraging the software supply chain Platform Support Sales motion and significantly contribute to the customer journey to build technical wins and championship Train our customers, prospects and community about product offering and solutions Represent the company in events and conferences Influence the features and roadmap of products based on customer needs Stay current with the latest technology trends related to the DevOps and DevSecOps landscape Join a company trusted by thousands of enterprise customers software engineering teams to deliver secure continuous updates, and is used by the majority of the Fortune 100, and help shape the future of secure and efficient software delivery. Opus Resourcing acts as an employment agency with respect to permanent employment. Skills: CI/CD, AZURE, GIT, DEVOPS, DOCKER, KUBERNETES, AWS,presales,Security,cloud platforms,Application Security,SAST,Sales Engineering,Technical Sales Consulting,Pre-Sales Technical Consulting
We are looking for an excellent ML Ops Engineer to join our research and development team. Key Responsibilities This opportunity is to join the ML Operations teams which supports the ML Development team in building leading-edge motion capture products through provisioning and maintaining a modern ML Operations stack. This stack covers data acquisition pipelines, data management and ML model training infrastructure (SW and on-prem HW). We use both on-prem, self-managed systems and also leverage AWS infrastructure. You will have opportunities to guide the technical direction of the ML Ops team, suggest new areas of development and the potential to lead your own project. Required Skills, Knowledge and Expertise You will have relevant academic (research Masters level) and/or industry experience. Excellent knowledge and experience of managing an on-premise Kubenetes cluster. Excellent knowledge of Kubeflow and similar systems, e.g. MLflow Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ML toolkits, e.g. PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools. Be able to design and implement MLOps solutions covering many different technologies. Desirable Skills Background in DevOps with exposure to CI systems, e.g. Jenkins Familiarity with infrastructure as code, e.g. Ansible Experience, aptitude, and a desire to work with human motion, sport, animation tools and techniques. Familiarity with C++.
03/10/2025
Full time
We are looking for an excellent ML Ops Engineer to join our research and development team. Key Responsibilities This opportunity is to join the ML Operations teams which supports the ML Development team in building leading-edge motion capture products through provisioning and maintaining a modern ML Operations stack. This stack covers data acquisition pipelines, data management and ML model training infrastructure (SW and on-prem HW). We use both on-prem, self-managed systems and also leverage AWS infrastructure. You will have opportunities to guide the technical direction of the ML Ops team, suggest new areas of development and the potential to lead your own project. Required Skills, Knowledge and Expertise You will have relevant academic (research Masters level) and/or industry experience. Excellent knowledge and experience of managing an on-premise Kubenetes cluster. Excellent knowledge of Kubeflow and similar systems, e.g. MLflow Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ML toolkits, e.g. PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools. Be able to design and implement MLOps solutions covering many different technologies. Desirable Skills Background in DevOps with exposure to CI systems, e.g. Jenkins Familiarity with infrastructure as code, e.g. Ansible Experience, aptitude, and a desire to work with human motion, sport, animation tools and techniques. Familiarity with C++.
Senior Machine Learning Engineer - Behavioural Modeling & Threat Detection - £150,000 - £180,000 - Fully Remote UK BASED CANDIDATES ONLY My client is looking for an experienced Machine Learning Engineer ready to play a pivotal role in shaping the technical direction of their behavioural modelling and threat detection systems. This position offers the opportunity to influence not just their engineering roadmap, but how they fundamentally approach solving complex, real-world security challenges with data. You'll work at the intersection of data science, ML infrastructure, and product innovation, leading efforts to build and evolve ML-driven capabilities, while also ensuring the reliability and scalability of their models in production environments. What You'll Do Spearhead the design and refinement of machine learning models focused on understanding behaviour patterns and identifying cybersecurity anomalies. Partner with product, engineering, and domain experts to translate strategic goals and customer needs into practical, scalable ML solutions. Drive model development end-to-end, from exploratory analysis, feature design, and prototyping to validation and deployment. Collaborate with platform and infra teams to operationalize models and ship ML-powered features into production. Continuously assess and iterate on production models, balancing long-term ML strategy with tactical improvements. Champion code quality, observability, and resilience within their ML systems through reviews and hands-on contributions. Help shape their internal ML standards and practices, ensuring they stay ahead of industry advancements. Offer technical mentorship and be a thought partner to colleagues across data, ML, and engineering disciplines. What We're Looking For Hands-on experience in developing and deploying machine learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially in cross-functional contexts. Bonus Experience (Nice to Have) Exposure to large language models (LLMs) or foundational model adaptation. Previous work in cybersecurity, anomaly detection, or behavioural analytics. Familiarity with orchestration frameworks (Airflow or similar). Experience with scalable ML systems, pipelines, or real-time data processing. Advanced degree or equivalent experience in ML/AI research or applied science. Cloud platform proficiency (AWS, GCP, Azure). If this sounds like something you would be interested in, please apply with your latest CV, a number to reach you on and I will be in touch. Alternatively, you can email me at . RSG Plc is acting as an Employment Agency in relation to this vacancy.
02/10/2025
Full time
Senior Machine Learning Engineer - Behavioural Modeling & Threat Detection - £150,000 - £180,000 - Fully Remote UK BASED CANDIDATES ONLY My client is looking for an experienced Machine Learning Engineer ready to play a pivotal role in shaping the technical direction of their behavioural modelling and threat detection systems. This position offers the opportunity to influence not just their engineering roadmap, but how they fundamentally approach solving complex, real-world security challenges with data. You'll work at the intersection of data science, ML infrastructure, and product innovation, leading efforts to build and evolve ML-driven capabilities, while also ensuring the reliability and scalability of their models in production environments. What You'll Do Spearhead the design and refinement of machine learning models focused on understanding behaviour patterns and identifying cybersecurity anomalies. Partner with product, engineering, and domain experts to translate strategic goals and customer needs into practical, scalable ML solutions. Drive model development end-to-end, from exploratory analysis, feature design, and prototyping to validation and deployment. Collaborate with platform and infra teams to operationalize models and ship ML-powered features into production. Continuously assess and iterate on production models, balancing long-term ML strategy with tactical improvements. Champion code quality, observability, and resilience within their ML systems through reviews and hands-on contributions. Help shape their internal ML standards and practices, ensuring they stay ahead of industry advancements. Offer technical mentorship and be a thought partner to colleagues across data, ML, and engineering disciplines. What We're Looking For Hands-on experience in developing and deploying machine learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially in cross-functional contexts. Bonus Experience (Nice to Have) Exposure to large language models (LLMs) or foundational model adaptation. Previous work in cybersecurity, anomaly detection, or behavioural analytics. Familiarity with orchestration frameworks (Airflow or similar). Experience with scalable ML systems, pipelines, or real-time data processing. Advanced degree or equivalent experience in ML/AI research or applied science. Cloud platform proficiency (AWS, GCP, Azure). If this sounds like something you would be interested in, please apply with your latest CV, a number to reach you on and I will be in touch. Alternatively, you can email me at . RSG Plc is acting as an Employment Agency in relation to this vacancy.
Director of AI Manchester (Office Based) Excellent Salary + Bonus + Benefits Are you a visionary AI leader ready to shape the future of enterprise AI; from strategic roadmap to hands-on implementation? Join a fast-scaling, international SaaS company that's transforming its industry through relentless innovation, advanced product development and investment in next-generation AI solutions. This is a rare, high-impact opportunity to define and drive the end-to-end AI agenda of a multi-award-winning business backed by a world-class leadership team. As Director of AI, you will own the company's AI vision - leading strategy development, technical execution, and operational scaling across Machine Learning, Generative AI, Large language Models and beyond. Your leadership will directly influence product innovation, operational excellence, and commercial success. Role Overview Define and drive the enterprise AI strategy - identifying opportunities for innovation, automation, and market differentiation using advanced AI/ML technologies. Own the full lifecycle of AI initiatives, from vision and roadmap to technical architecture, delivery, optimisation, and governance. Build and lead cross-functional AI teams, ensuring alignment between technical execution and strategic business goals. Evaluate emerging technologies (e.g. LLMs, RAG, vector search, knowledge graphs) and make evidence-based recommendations to stakeholders. Establish best practices for responsible AI development, including risk management, compliance, and explainability. Partner with senior leadership to integrate AI into core business functions and customer-facing products at speed and scale. What You Bring Proven leadership in delivering enterprise-scale AI strategies, ideally in a high-growth SaaS or technology-led environment. Strong academic or practical background in AI, ML, Data Science, Computer Science or a related STEM field. Demonstrated hands-on expertise in building and deploying advanced ML and Generative AI models in production (including RAG Architecture) Deep technical proficiency with LLMs, NLP, Python, SQL, and major AI/ML frameworks (e.g., PyTorch, TensorFlow). Strong understanding of AI engineering fundamentals including DevOps, CI/CD, MLOps, and DevSecOps. Experience building AI governance frameworks to address ethical risk, model accuracy, and regulatory compliance. Why Join? This is a career-defining opportunity to shape the AI strategy of a high-growth, global and entrepreneurial organisation. You'll work alongside a visionary leadership team and have the autonomy to innovate, influence, and scale AI solutions that have real-world commercial impact. Enjoy a highly competitive compensation package, including: Excellent base salary Generous performance-based bonus Private healthcare, pension scheme, and premium benefits A dynamic, innovation-first culture with real career progression DAI(phone number removed)AM INDAMS
02/10/2025
Full time
Director of AI Manchester (Office Based) Excellent Salary + Bonus + Benefits Are you a visionary AI leader ready to shape the future of enterprise AI; from strategic roadmap to hands-on implementation? Join a fast-scaling, international SaaS company that's transforming its industry through relentless innovation, advanced product development and investment in next-generation AI solutions. This is a rare, high-impact opportunity to define and drive the end-to-end AI agenda of a multi-award-winning business backed by a world-class leadership team. As Director of AI, you will own the company's AI vision - leading strategy development, technical execution, and operational scaling across Machine Learning, Generative AI, Large language Models and beyond. Your leadership will directly influence product innovation, operational excellence, and commercial success. Role Overview Define and drive the enterprise AI strategy - identifying opportunities for innovation, automation, and market differentiation using advanced AI/ML technologies. Own the full lifecycle of AI initiatives, from vision and roadmap to technical architecture, delivery, optimisation, and governance. Build and lead cross-functional AI teams, ensuring alignment between technical execution and strategic business goals. Evaluate emerging technologies (e.g. LLMs, RAG, vector search, knowledge graphs) and make evidence-based recommendations to stakeholders. Establish best practices for responsible AI development, including risk management, compliance, and explainability. Partner with senior leadership to integrate AI into core business functions and customer-facing products at speed and scale. What You Bring Proven leadership in delivering enterprise-scale AI strategies, ideally in a high-growth SaaS or technology-led environment. Strong academic or practical background in AI, ML, Data Science, Computer Science or a related STEM field. Demonstrated hands-on expertise in building and deploying advanced ML and Generative AI models in production (including RAG Architecture) Deep technical proficiency with LLMs, NLP, Python, SQL, and major AI/ML frameworks (e.g., PyTorch, TensorFlow). Strong understanding of AI engineering fundamentals including DevOps, CI/CD, MLOps, and DevSecOps. Experience building AI governance frameworks to address ethical risk, model accuracy, and regulatory compliance. Why Join? This is a career-defining opportunity to shape the AI strategy of a high-growth, global and entrepreneurial organisation. You'll work alongside a visionary leadership team and have the autonomy to innovate, influence, and scale AI solutions that have real-world commercial impact. Enjoy a highly competitive compensation package, including: Excellent base salary Generous performance-based bonus Private healthcare, pension scheme, and premium benefits A dynamic, innovation-first culture with real career progression DAI(phone number removed)AM INDAMS
Amass Technology's client is looking for a Graph Engineer/Data Ontology Specialist on a contract basis to start ASAP. See details below: All applicants must be UK based. Key Responsibilities Design, optimise, and query graph databases (particularly Amazon Neptune). Develop and manage ontologies and robust knowledge representation frameworks. Integrate LLMs (Claude 3.7 or above, GPT, etc.) for content analysis, entity extraction, and semantic enrichment. Implement Retrieval Augmented Generation (RAG) and LLM-based fact extraction ([Subject, Verb, Object] triples). Build LLM-assisted QA pipelines for relationship validation and data consistency. Fine-tune and customise models for domain-specific applications. Apply graph algorithms, graph neural networks, and reasoning within Neptune and knowledge graph environments. Develop vector-based similarity search using embeddings and similarity algorithms. Apply traditional NLP methods (NER, POS tagging, syntactic parsing) alongside LLMs. Use clustering, classification, anomaly detection, and time-series analysis for content analysis and quality assurance. Deploy and scale ML models in production environments using AWS AI/ML services (eg, SageMaker). Build and optimise ETL pipelines and data workflows for large, complex datasets. Work with RDF, SPARQL, and semantic web technologies for structured data management. Required Skills & Expertise Graph engineering with Amazon Neptune and knowledge graph frameworks. Ontology engineering and semantic data modelling. LLM integration, fine-tuning, and RAG pipeline implementation. Advanced NLP and information retrieval methods. Experience with graph-based AI techniques (algorithms, GNNs, reasoning). Strong MLOps skills in performance evaluation and pipeline automation. Proficiency in AWS ML ecosystem (SageMaker, AI/ML services). Experience in ETL/data pipelines, semantic web standards (RDF, SPARQL). This is an excellent opportunity to work with some of the latest technologies on a really interesting project If you have the right experience and are looking for a new role, please send in your CV.
01/10/2025
Contractor
Amass Technology's client is looking for a Graph Engineer/Data Ontology Specialist on a contract basis to start ASAP. See details below: All applicants must be UK based. Key Responsibilities Design, optimise, and query graph databases (particularly Amazon Neptune). Develop and manage ontologies and robust knowledge representation frameworks. Integrate LLMs (Claude 3.7 or above, GPT, etc.) for content analysis, entity extraction, and semantic enrichment. Implement Retrieval Augmented Generation (RAG) and LLM-based fact extraction ([Subject, Verb, Object] triples). Build LLM-assisted QA pipelines for relationship validation and data consistency. Fine-tune and customise models for domain-specific applications. Apply graph algorithms, graph neural networks, and reasoning within Neptune and knowledge graph environments. Develop vector-based similarity search using embeddings and similarity algorithms. Apply traditional NLP methods (NER, POS tagging, syntactic parsing) alongside LLMs. Use clustering, classification, anomaly detection, and time-series analysis for content analysis and quality assurance. Deploy and scale ML models in production environments using AWS AI/ML services (eg, SageMaker). Build and optimise ETL pipelines and data workflows for large, complex datasets. Work with RDF, SPARQL, and semantic web technologies for structured data management. Required Skills & Expertise Graph engineering with Amazon Neptune and knowledge graph frameworks. Ontology engineering and semantic data modelling. LLM integration, fine-tuning, and RAG pipeline implementation. Advanced NLP and information retrieval methods. Experience with graph-based AI techniques (algorithms, GNNs, reasoning). Strong MLOps skills in performance evaluation and pipeline automation. Proficiency in AWS ML ecosystem (SageMaker, AI/ML services). Experience in ETL/data pipelines, semantic web standards (RDF, SPARQL). This is an excellent opportunity to work with some of the latest technologies on a really interesting project If you have the right experience and are looking for a new role, please send in your CV.
Director of Machine Learning & AI Location: London/Remote Package: Strong Salary + Benefits We're partnered with a fast-growing tech business that's investing heavily in its AI capability. They're looking for a proven ML/AI leader who can take charge of multiple high-performing teams and set the direction for how Machine Learning is built and scaled across the organisation. This isn't about "experiments in the corner", it's about shaping strategy, leading delivery, and putting advanced ML systems into production where they make a measurable difference. What you'll be doing: Leading and scaling cross-functional teams (Data Science, ML Engineering, Software Engineering, Managers). Defining the ML/AI roadmap and aligning it to business outcomes. Driving best practice in MLOps, deployment, observability, and automation. Working with cutting-edge approaches: deep learning frameworks, foundation models, knowledge graphs, etc. Being the voice of ML/AI leadership, setting standards, mentoring, and building a culture of delivery. What they're looking for: You've built and run ML teams at scale, and delivered systems into production, not just research. Technical depth in modern ML/AI (from LLMs to advanced ML infra). Strong grasp of cloud-native, containerised environments and modern engineering practice. Credibility with both exec stakeholders and engineers, you can set strategy and still talk technical detail when needed. Bonus if you've operated in complex, regulated, or high-transaction environments. Why this role: Serious investment in AI/ML High autonomy and direct impact on how the organisation uses ML at scale Forward-looking culture: growth budget for self-development, modern tech stack, flexibility in where and how you work. A chance to define and own the ML strategy in a business that sees it as a competitive edge, not a side project. If you're a Machine Learning Director who wants to be at the centre of a real AI build-out; leading teams, shaping strategy, and delivering meaningful impact, this is one of those rare opportunities. Director of Machine Learning & AI RSG Plc is acting as an Employment Agency in relation to this vacancy.
01/10/2025
Full time
Director of Machine Learning & AI Location: London/Remote Package: Strong Salary + Benefits We're partnered with a fast-growing tech business that's investing heavily in its AI capability. They're looking for a proven ML/AI leader who can take charge of multiple high-performing teams and set the direction for how Machine Learning is built and scaled across the organisation. This isn't about "experiments in the corner", it's about shaping strategy, leading delivery, and putting advanced ML systems into production where they make a measurable difference. What you'll be doing: Leading and scaling cross-functional teams (Data Science, ML Engineering, Software Engineering, Managers). Defining the ML/AI roadmap and aligning it to business outcomes. Driving best practice in MLOps, deployment, observability, and automation. Working with cutting-edge approaches: deep learning frameworks, foundation models, knowledge graphs, etc. Being the voice of ML/AI leadership, setting standards, mentoring, and building a culture of delivery. What they're looking for: You've built and run ML teams at scale, and delivered systems into production, not just research. Technical depth in modern ML/AI (from LLMs to advanced ML infra). Strong grasp of cloud-native, containerised environments and modern engineering practice. Credibility with both exec stakeholders and engineers, you can set strategy and still talk technical detail when needed. Bonus if you've operated in complex, regulated, or high-transaction environments. Why this role: Serious investment in AI/ML High autonomy and direct impact on how the organisation uses ML at scale Forward-looking culture: growth budget for self-development, modern tech stack, flexibility in where and how you work. A chance to define and own the ML strategy in a business that sees it as a competitive edge, not a side project. If you're a Machine Learning Director who wants to be at the centre of a real AI build-out; leading teams, shaping strategy, and delivering meaningful impact, this is one of those rare opportunities. Director of Machine Learning & AI RSG Plc is acting as an Employment Agency in relation to this vacancy.
MACHINE LEARNING ENGINEER (MLOPS)
HYBRID/EDINBURGH OR UK REMOTE £55-60,000 PLUS BENEFITS
Based in Edinburgh, GRW Talent’s client is considered to be the leading audio-driven facial animation provider in the video-game industry. They employ detailed muscle maps for extremely accurate real-time lip-sync, trading across two recognised brands. One is an innovative platform that integrates AI with animated digital characters, enabling engaging and meaningful interactions in any language. This platform is being used to bring best-in-class digital experiences to multiple sectors, including corporate training, immersive learning, and virtual influencers.
With a culture that thrives on collaboration, creativity and pushing technological boundaries, they are committed to providing a workplace where people can grow, innovate and make an impact. They now need to recruit an experienced Machine Learning Engineer (MLOPS).
As a Senior Machine Learning Engineer (MLOps) at you will be responsible for driving the vision and implementation of MLOps pipelines and best practices. You will support the Research team by developing and maintaining the internal machine learning platform, ensuring seamless model deployment, and resolving technical issues or bugs as they arise. This role is critical in ensuring the accuracy, efficiency, and reliability of our machine learning operations, which are essential for the development and deployment of our speech animation technologies. Note that this role doesn’t involve hands-on model training. Key responsibilities include:
Drive the vision and implementation of MLOps pipelines and best practices to ensure efficient and scalable machine learning operations.
Assume a leadership role in projects, overseeing various project planning and management responsibilities.
Develop and maintain internal tools, including the machine learning platform and python libraries.
Collaborate closely with the research team to gather their requirements and provide technical support.
Implement algorithms to support research needs.
Identify, troubleshoot, and resolve technical problems and bugs promptly.
Maintain list of third party libraries dependencies to ensure compliance with information security and licensing standards.
Write and optimise production-ready code for product deployments.
Contribute to continuous integration/continuous deployment (CI/CD) for MLOps components.
Provide guidance and maintain comprehensive technical documentation to ensure knowledge sharing and operational continuity.
The relevant candidate is educated to degree calibre in Computer Science, Software Engineering or Data Science. You are a proven Machine Learning Engineer / MLOPS, with expertise in ML platform development and model deployment, experience in establishing and improving MLOps processes, strong Python development skills and experience with a machine learning toolkit, preferably PyTorch. Familiarity with any of the following domains: signal processing, speech technology, linguistics, and mathematical optimization would be a distinct advantage.
This role represent an excellent opportunity for an aspiring and experienced Machine Learning Engineer to drive the growth of a highly successful Scottish SME in the busy gaming space. Your base salary £55-60,000 is complemented by company pension, 33 days off, free food and drink in the office, self improvement budget and learning opportunities, healthcare benefits and a fun highly social culture and environment. Our client would welcome someone who wants to come into a friendly outgoing Edinburgh office, but you could also do this remotely as long as you are free to live and work in the UK.
To apply to this role please contact our recruitment partner Bruce Hydes at GRw Talent
01/06/2025
MACHINE LEARNING ENGINEER (MLOPS)
HYBRID/EDINBURGH OR UK REMOTE £55-60,000 PLUS BENEFITS
Based in Edinburgh, GRW Talent’s client is considered to be the leading audio-driven facial animation provider in the video-game industry. They employ detailed muscle maps for extremely accurate real-time lip-sync, trading across two recognised brands. One is an innovative platform that integrates AI with animated digital characters, enabling engaging and meaningful interactions in any language. This platform is being used to bring best-in-class digital experiences to multiple sectors, including corporate training, immersive learning, and virtual influencers.
With a culture that thrives on collaboration, creativity and pushing technological boundaries, they are committed to providing a workplace where people can grow, innovate and make an impact. They now need to recruit an experienced Machine Learning Engineer (MLOPS).
As a Senior Machine Learning Engineer (MLOps) at you will be responsible for driving the vision and implementation of MLOps pipelines and best practices. You will support the Research team by developing and maintaining the internal machine learning platform, ensuring seamless model deployment, and resolving technical issues or bugs as they arise. This role is critical in ensuring the accuracy, efficiency, and reliability of our machine learning operations, which are essential for the development and deployment of our speech animation technologies. Note that this role doesn’t involve hands-on model training. Key responsibilities include:
Drive the vision and implementation of MLOps pipelines and best practices to ensure efficient and scalable machine learning operations.
Assume a leadership role in projects, overseeing various project planning and management responsibilities.
Develop and maintain internal tools, including the machine learning platform and python libraries.
Collaborate closely with the research team to gather their requirements and provide technical support.
Implement algorithms to support research needs.
Identify, troubleshoot, and resolve technical problems and bugs promptly.
Maintain list of third party libraries dependencies to ensure compliance with information security and licensing standards.
Write and optimise production-ready code for product deployments.
Contribute to continuous integration/continuous deployment (CI/CD) for MLOps components.
Provide guidance and maintain comprehensive technical documentation to ensure knowledge sharing and operational continuity.
The relevant candidate is educated to degree calibre in Computer Science, Software Engineering or Data Science. You are a proven Machine Learning Engineer / MLOPS, with expertise in ML platform development and model deployment, experience in establishing and improving MLOps processes, strong Python development skills and experience with a machine learning toolkit, preferably PyTorch. Familiarity with any of the following domains: signal processing, speech technology, linguistics, and mathematical optimization would be a distinct advantage.
This role represent an excellent opportunity for an aspiring and experienced Machine Learning Engineer to drive the growth of a highly successful Scottish SME in the busy gaming space. Your base salary £55-60,000 is complemented by company pension, 33 days off, free food and drink in the office, self improvement budget and learning opportunities, healthcare benefits and a fun highly social culture and environment. Our client would welcome someone who wants to come into a friendly outgoing Edinburgh office, but you could also do this remotely as long as you are free to live and work in the UK.
To apply to this role please contact our recruitment partner Bruce Hydes at GRw Talent
Machine Learning Engineer
Up to £70K DOE
Hybrid – London (2 days per week onsite)
My client is looking for a Junior to Mid-Level Machine Learning Engineer to take ownership of the infrastructure and services that power machine learning systems in production. In this role, you’ll act as a bridge between data science and engineering, ensuring robust, scalable, and low-latency deployment of models that serve millions of requests per day.
You’ll be responsible for building and maintaining Python microservices, leveraging modern DevOps practices and tooling to support rapid, reliable delivery. With sub-second response times and a high-throughput environment (2M+ requests/day), this is a high-impact role that blends software engineering, DevOps, and MLOps at scale.
Key Responsibilities
* Design, develop, and maintain Python microservices for serving machine learning models
* Collaborate with Data Scientists to deploy, monitor, and support models in production
* Implement and manage CI/CD pipelines using Azure DevOps
* Support containerized deployments with Kubernetes and Docker
* Ensure high performance, fault-tolerant, and secure infrastructure
* Promote code quality, testing standards, and scalable architecture
* Proactively identify infrastructure improvements and lead implementation
Requirements
* 2 + years of experience in Software Engineering, DevOps, or Data Engineering
* Strong Python skills with experience in microservices and web frameworks
* Solid understanding of CI/CD, ideally using Azure DevOps
* Familiarity with containerized environments (Docker/Kubernetes)
* Exposure to Data Science or Machine Learning concepts
* Experience operating in high-throughput environments
* Independent, curious, and driven by continuous improvement
* Effective communicator with the ability to bridge data science and engineering teams
Why Join?
You’ll be joining a company with strong business performance and ambitious plans for data-driven growth. This is a rare opportunity to take technical ownership of real-time machine learning infrastructure and play a key role in scaling systems that make an immediate business impact
01/06/2025
Machine Learning Engineer
Up to £70K DOE
Hybrid – London (2 days per week onsite)
My client is looking for a Junior to Mid-Level Machine Learning Engineer to take ownership of the infrastructure and services that power machine learning systems in production. In this role, you’ll act as a bridge between data science and engineering, ensuring robust, scalable, and low-latency deployment of models that serve millions of requests per day.
You’ll be responsible for building and maintaining Python microservices, leveraging modern DevOps practices and tooling to support rapid, reliable delivery. With sub-second response times and a high-throughput environment (2M+ requests/day), this is a high-impact role that blends software engineering, DevOps, and MLOps at scale.
Key Responsibilities
* Design, develop, and maintain Python microservices for serving machine learning models
* Collaborate with Data Scientists to deploy, monitor, and support models in production
* Implement and manage CI/CD pipelines using Azure DevOps
* Support containerized deployments with Kubernetes and Docker
* Ensure high performance, fault-tolerant, and secure infrastructure
* Promote code quality, testing standards, and scalable architecture
* Proactively identify infrastructure improvements and lead implementation
Requirements
* 2 + years of experience in Software Engineering, DevOps, or Data Engineering
* Strong Python skills with experience in microservices and web frameworks
* Solid understanding of CI/CD, ideally using Azure DevOps
* Familiarity with containerized environments (Docker/Kubernetes)
* Exposure to Data Science or Machine Learning concepts
* Experience operating in high-throughput environments
* Independent, curious, and driven by continuous improvement
* Effective communicator with the ability to bridge data science and engineering teams
Why Join?
You’ll be joining a company with strong business performance and ambitious plans for data-driven growth. This is a rare opportunity to take technical ownership of real-time machine learning infrastructure and play a key role in scaling systems that make an immediate business impact