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.
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.
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
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
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
My Client are seeking a Senior Data Scientist to join the team on a permanent basis specialising in ontology, knowledge engineering, knowledge graphs, and more. This role is not for the faint-hearted but for those energised by challenges, inspired by innovation, and driven by real-world impact. The role can pay up to £80,000 per annum for the right person so please click apply if you feel the below suits your skill set: Qualifications: Education: MSc/PhD in Data Science, Computer Science, or related field Experience: 5-7 years of hands-on experience in the industrySkills: Deep knowledge in First-Order Logic, Descriptive Logic, Web Ontology Language (OWL) Proficiency in graph neural networks (GNN), network science, and semantic networks Mastery over task-specific finetuning, including data extraction, classification, and generation A comprehensive understanding of traditional statistics, Machine Learning (ML), and multi-objective optimisation techniques Excellent communication and written skills Passion for continuous learning and collaboration as a team player Tools: Python: Structured workflows using environments, Conda, Git, GitFlow, etc.Databases: Traditional (SQL) and Graph Databases (openCypher, Gremlin, SPARQL) Technologies: MLOps/LLMOps, Protege, Cloud environments (Azure/AWS)
15/08/2023
Full time
My Client are seeking a Senior Data Scientist to join the team on a permanent basis specialising in ontology, knowledge engineering, knowledge graphs, and more. This role is not for the faint-hearted but for those energised by challenges, inspired by innovation, and driven by real-world impact. The role can pay up to £80,000 per annum for the right person so please click apply if you feel the below suits your skill set: Qualifications: Education: MSc/PhD in Data Science, Computer Science, or related field Experience: 5-7 years of hands-on experience in the industrySkills: Deep knowledge in First-Order Logic, Descriptive Logic, Web Ontology Language (OWL) Proficiency in graph neural networks (GNN), network science, and semantic networks Mastery over task-specific finetuning, including data extraction, classification, and generation A comprehensive understanding of traditional statistics, Machine Learning (ML), and multi-objective optimisation techniques Excellent communication and written skills Passion for continuous learning and collaboration as a team player Tools: Python: Structured workflows using environments, Conda, Git, GitFlow, etc.Databases: Traditional (SQL) and Graph Databases (openCypher, Gremlin, SPARQL) Technologies: MLOps/LLMOps, Protege, Cloud environments (Azure/AWS)
Job Introduction BBC R&D has recently established an Automation Applied Research Area focussed on the use of Machine Learning across the BBC. Automation works closely with other BBC R&D Applied Research Areas, BBC Product and Technology Groups and senior business stakeholders across the BBC to accelerate Machine Learning based innovation. Reporting to the Head of Automation, this role will lead a team of experts exploring the ML platforms, tools, performance, and sustainability that will underpin the BBC's approach to Machine Learning innovation. It will ensure that best practice and correct technology choices are downstreamed into R&D ML applications as well as supporting the wider BBC in making the right strategic decisions for its future ML technology. BBC R&D has five applied research areas focussed on Audiences, Automation, Distribution, Infrastructure and Production who are looking to solve some of the most interesting challenges in Media and Broadcasting; as well as our Commercial, Partnerships & Engagement team who ensure we're collaborating with the right external partners and optimising commercial returns through the exploitation of our Intellectual Property and grant funding. Our work supports the BBC's current ambition as well as informing future strategy. If you're excited by the prospect of working in an innovative environment with smart and supportive colleagues, then BBC R&D is the place for you. Role Responsibility This is a hands-on role. Your key responsibilities will be: Build and lead a team of ML engineers to develop an infrastructure to manage ML lifecycle through experimentation, deployment, and testing. Own the Automation MLOps strategy, roadmap, and backlog. Provide leadership and guidance on the delivery of ML models from prototypes to production, mentor and coach team members on ML engineering best practises; work alongside researchers to enable BBC to benefit more rapidly from fundamental ML research. Contribute to the design of ML systems and infrastructure to shape how ML is used across the BBC. Develop relationships with pan-BBC and external contributors and stakeholders. You will need to bring to life long-term ambitions to secure required support and buy-in for tangible and intangible benefits and outcomes. Focus on ensuring our ML technology delivers on performance, cost and sustainability goals and is supportive of the BBC's responsible and ethical ML objectives. Work with our Technology Strategy and Governance team to identify and communicate strategic investment decisions required to mature the BBC's ML technology in line with business needs. Are you the right candidate? Solid understanding of machine learning concepts and algorithms Experience deploying machine learning solutions Expert knowledge of Python programming and machine learning libraries (Scikit-learn, TensorFlow, Keras, PyTorch, MxNet, etc.) Experience implementing ML automation, MLOps (scalable deployment practices aimed to deploy and maintain machine learning models in production reliably and efficiently) and related tools (e.g., MLflow, Kubeflow, Airflow, Sagemaker) Experience working in accordance with DevOps principles, and with industry deployment best practices using CI/CD tools and infrastructure as code (e.g., Docker, Kubernetes, Terraform) Experience in at least one cloud platform (e.g., AWS, GCP, Azure) and associated machine learning services, e.g., Amazon SageMaker, Azure ML, Databricks. Package Description Band: E Contract type: Permanent - Full time Location: UK wide We're happy to discuss flexible working. Please indicate your choice under the flexible working question in the application . There is no obligation to raise this at the application stage but if you wish to do so, you are welcome to. Flexible working will be part of the discussion at offer stage. Excellent career progression - the BBC offers great opportunities for employees to seek new challenges and work in different areas of the organisation. Unrivalled training and development opportunities - our in-house Academy hosts a wide range of internal and external courses and certification. Benefits - We offer a competitive salary package, a flexible 35-hour working week for work-life balance and 26 days (1 of which is a corporation day) with the option to buy an extra 5 days, a defined pension scheme and discounted dental, health care, gym and much more. The situation regarding the coronavirus outbreak is developing quickly and the BBC is keen to continue to ensure the safety and wellbeing of people across the BBC, while continuing to protect our services. To reduce the risk access to BBC buildings is limited to those essential to our broadcast output. From Wednesday 18 th March until further notice all assessments and interviews will be conducted remotely. For more information go to Mae'r sefyllfa gyda'r coronafeirws yn datblygu'n gyflym, ac mae'r BBC yn awyddus i barhau i sicrhau diogelwch a lles pobl ar draws y BBC, gan barhau i warchod ein gwasanaethau hefyd. I leihau'r risg, dim ond y bobl sy'n hanfodol i'n hallbwn darlledu fydd yn cael mynediad i adeiladau'r BBC. O ddydd Mercher 18 fed Mawrth ymlaen, bydd pob asesiad a chyfweliad yn cael ei gynnal o bell, nes rhoddir gwybod yn wahanol. I gael mwy o wybodaeth, ewch i About the BBC We don't focus simply on what we do - we also care how we do it. Our values and the way we behave are important to us. Please make sure you've read about our values and behaviours in the document attached below. Diversity matters at the BBC. We have a working environment where we value and respect every individual's unique contribution, enabling all of our employees to thrive and achieve their full potential. We want to attract the broadest range of talented people to be part of the BBC - whether that's to contribute to our programming or our wide range of non-production roles. The more diverse our workforce, the better able we are to respond to and reflect our audiences in all their diversity. We are committed to equality of opportunity and welcome applications from individuals, regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion and/or belief. We will consider flexible working requests for all roles, unless operational requirements prevent otherwise. To find out more about Diversity and Inclusion at the BBC, please click here
23/09/2022
Full time
Job Introduction BBC R&D has recently established an Automation Applied Research Area focussed on the use of Machine Learning across the BBC. Automation works closely with other BBC R&D Applied Research Areas, BBC Product and Technology Groups and senior business stakeholders across the BBC to accelerate Machine Learning based innovation. Reporting to the Head of Automation, this role will lead a team of experts exploring the ML platforms, tools, performance, and sustainability that will underpin the BBC's approach to Machine Learning innovation. It will ensure that best practice and correct technology choices are downstreamed into R&D ML applications as well as supporting the wider BBC in making the right strategic decisions for its future ML technology. BBC R&D has five applied research areas focussed on Audiences, Automation, Distribution, Infrastructure and Production who are looking to solve some of the most interesting challenges in Media and Broadcasting; as well as our Commercial, Partnerships & Engagement team who ensure we're collaborating with the right external partners and optimising commercial returns through the exploitation of our Intellectual Property and grant funding. Our work supports the BBC's current ambition as well as informing future strategy. If you're excited by the prospect of working in an innovative environment with smart and supportive colleagues, then BBC R&D is the place for you. Role Responsibility This is a hands-on role. Your key responsibilities will be: Build and lead a team of ML engineers to develop an infrastructure to manage ML lifecycle through experimentation, deployment, and testing. Own the Automation MLOps strategy, roadmap, and backlog. Provide leadership and guidance on the delivery of ML models from prototypes to production, mentor and coach team members on ML engineering best practises; work alongside researchers to enable BBC to benefit more rapidly from fundamental ML research. Contribute to the design of ML systems and infrastructure to shape how ML is used across the BBC. Develop relationships with pan-BBC and external contributors and stakeholders. You will need to bring to life long-term ambitions to secure required support and buy-in for tangible and intangible benefits and outcomes. Focus on ensuring our ML technology delivers on performance, cost and sustainability goals and is supportive of the BBC's responsible and ethical ML objectives. Work with our Technology Strategy and Governance team to identify and communicate strategic investment decisions required to mature the BBC's ML technology in line with business needs. Are you the right candidate? Solid understanding of machine learning concepts and algorithms Experience deploying machine learning solutions Expert knowledge of Python programming and machine learning libraries (Scikit-learn, TensorFlow, Keras, PyTorch, MxNet, etc.) Experience implementing ML automation, MLOps (scalable deployment practices aimed to deploy and maintain machine learning models in production reliably and efficiently) and related tools (e.g., MLflow, Kubeflow, Airflow, Sagemaker) Experience working in accordance with DevOps principles, and with industry deployment best practices using CI/CD tools and infrastructure as code (e.g., Docker, Kubernetes, Terraform) Experience in at least one cloud platform (e.g., AWS, GCP, Azure) and associated machine learning services, e.g., Amazon SageMaker, Azure ML, Databricks. Package Description Band: E Contract type: Permanent - Full time Location: UK wide We're happy to discuss flexible working. Please indicate your choice under the flexible working question in the application . There is no obligation to raise this at the application stage but if you wish to do so, you are welcome to. Flexible working will be part of the discussion at offer stage. Excellent career progression - the BBC offers great opportunities for employees to seek new challenges and work in different areas of the organisation. Unrivalled training and development opportunities - our in-house Academy hosts a wide range of internal and external courses and certification. Benefits - We offer a competitive salary package, a flexible 35-hour working week for work-life balance and 26 days (1 of which is a corporation day) with the option to buy an extra 5 days, a defined pension scheme and discounted dental, health care, gym and much more. The situation regarding the coronavirus outbreak is developing quickly and the BBC is keen to continue to ensure the safety and wellbeing of people across the BBC, while continuing to protect our services. To reduce the risk access to BBC buildings is limited to those essential to our broadcast output. From Wednesday 18 th March until further notice all assessments and interviews will be conducted remotely. For more information go to Mae'r sefyllfa gyda'r coronafeirws yn datblygu'n gyflym, ac mae'r BBC yn awyddus i barhau i sicrhau diogelwch a lles pobl ar draws y BBC, gan barhau i warchod ein gwasanaethau hefyd. I leihau'r risg, dim ond y bobl sy'n hanfodol i'n hallbwn darlledu fydd yn cael mynediad i adeiladau'r BBC. O ddydd Mercher 18 fed Mawrth ymlaen, bydd pob asesiad a chyfweliad yn cael ei gynnal o bell, nes rhoddir gwybod yn wahanol. I gael mwy o wybodaeth, ewch i About the BBC We don't focus simply on what we do - we also care how we do it. Our values and the way we behave are important to us. Please make sure you've read about our values and behaviours in the document attached below. Diversity matters at the BBC. We have a working environment where we value and respect every individual's unique contribution, enabling all of our employees to thrive and achieve their full potential. We want to attract the broadest range of talented people to be part of the BBC - whether that's to contribute to our programming or our wide range of non-production roles. The more diverse our workforce, the better able we are to respond to and reflect our audiences in all their diversity. We are committed to equality of opportunity and welcome applications from individuals, regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion and/or belief. We will consider flexible working requests for all roles, unless operational requirements prevent otherwise. To find out more about Diversity and Inclusion at the BBC, please click here
Site Name: UK - Hertfordshire - Stevenage, USA - Connecticut - Hartford, USA - Delaware - Dover, USA - Maryland - Rockville, USA - Massachusetts - Cambridge, USA - Massachusetts - Waltham, USA - New Jersey - Trenton, USA - Pennsylvania - Upper Providence Posted Date: Jun 6 2022 The mission of the Data Science and Data Engineering (DSDE) organization within GSK Pharmaceuticals R&D is to get the right data, to the right people, at the right time. TheData Framework and Opsorganization ensures we can do this efficiently, reliably, transparently, and at scale through the creation of a leading-edge, cloud-native data services framework. We focus heavily on developer experience, on strong, semantic abstractions for the data ecosystem, on professional operations and aggressive automation, and on transparency of operations and cost. Achieving delivery of the right data to the right people at the right time needs design and implementation of data flows and data products which leverage internal and external data assets and tools to drive discovery and development is a key objective for the Data Science and Data Engineering (DSDE) team within GSK's Pharmaceutical R&D organization. There are five key drivers for this approach, which are closely aligned with GSK's corporate priorities of Innovation, Performance and Trust: Automation of end-to-end data flows :Faster and reliable ingestion of high throughput data in genetics, genomics and multi-omics, to extract value of investments in new technology (instrument to analysis-ready data in Enabling governance by design of external and internal data :with engineered practical solutions for controlled use and monitoring Innovative disease-specific and domain-expert specific data products : to enable computational scientists and their research unit collaborators to get faster to key insights leading to faster biopharmaceutical development cycles. Supporting e2ecode traceability and data provenance :Increasing assurance of data integrity through automation, integration. Improving engineering efficiency :Extensible, reusable, scalable,updateable,maintainable, virtualized traceable data and code would be driven by data engineering innovation and better resource utilization. We are looking for experienced Senior DevOps Engineers to join our growing Data Ops team. As a Senior Dev Ops Engineer is a highly technical individual contributor, building modern, cloud-native, DevOps-first systems for standardizing and templatizingbiomedical and scientificdata engineering, with demonstrable experience across the following areas: Deliver declarative components for common data ingestion, transformation and publishing techniques Define and implement data governance aligned to modern standards Establish scalable, automated processes for data engineering teams across GSK Thought leader and partner with wider DSDE data engineering teams to advise on implementation and best practices Cloud Infrastructure-as-Code Define Service and Flow orchestration Data as a configurable resource(including configuration-driven access to scientific data modelling tools) Observability (monitoring, alerting, logging, tracing, etc.) Enable quality engineering through KPIs and code coverage and quality checks Standardise GitOps/declarative software development lifecycle Audit as a service Senior DevOpsEngineers take full ownership of delivering high-performing, high-impactbiomedical and scientificdataopsproducts and services, froma description of apattern thatcustomer Data Engineers are trying touseall the way through tofinal delivery (and ongoing monitoring and operations)of a templated project and all associated automation. They arestandard-bearers for software engineering and quality coding practices within theteam andareexpected to mentor more junior engineers; they may even coordinate the work of more junior engineers on a large project.Theydevise useful metrics for ensuring their services are meeting customer demand and having animpact anditerate to deliver and improve on those metrics in an agile fashion. Successful Senior DevOpsEngineers are developing expertise with the types of data and types of tools that are leveraged in the biomedical and scientific data engineering space, andhas the following skills and experience(withsignificant depth in one or more of these areas): Demonstrable experience deploying robust modularised/container-based solutions to production (ideally GCP) and leveraging the Cloud NativeComputing Foundation (CNCF) ecosystem Significant depth in DevOps principles and tools (e.g.GitOps, Jenkins,CircleCI, Azure DevOps, etc.), and how to integrate these tools with other productivity tools (e.g. Jira, Slack, Microsoft Teams) to build a comprehensive workflow Programming in Python. Scala orGo Embedding agile software engineering (task/issue management, testing, documentation, software development lifecycle, source control, etc.) Leveraging major cloud providers, both via Kubernetesorvia vendor-specific services Authentication and Authorization flows and associated technologies (e.g.OAuth2 + JWT) Common distributed data tools (e.g.Spark, Hive) The DSDE team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career and development from day one. Why you? Basic Qualifications: We are looking for professionals with these required skills to achieve our goals: Masters in Computer Science with a focus in Data Engineering, DataOps, DevOps, MLOps, Software Engineering, etc, plus 5 years job experience (or PhD plus 3 years job experience) Experience with DevOps tools and concepts (e.g. Jira, GitLabs / Jenkins / CircleCI / Azure DevOps /etc.)Excellent with common distributed data tools in a production setting (Spark, Kafka, etc) Experience with specialized data architecture (e.g. optimizing physical layout for access patterns, including bloom filters, optimizing against self-describing formats such as ORC or Parquet, etc.) Experience with search / indexing systems (e.g. Elasticsearch) Expertise with agile development in Python, Scala, Go, and/or C++ Experience building reusable components on top of the CNCF ecosystem including Kubernetes Metrics-first mindset Experience mentoring junior engineers into deep technical expertise Preferred Qualifications: If you have the following characteristics, it would be a plus: Experience with agile software development Experience with building and designing a DevOps-first way of working Experience with building reusable components on top of the CNCF ecosystem including Kubernetes (or similar ecosystem ) LI-GSK Why GSK? Our values and expectationsare at the heart of everything we do and form an important part of our culture. These include Patient focus, Transparency, Respect, Integrity along with Courage, Accountability, Development, and Teamwork. As GSK focuses on our values and expectations and a culture of innovation, performance, and trust, the successful candidate will demonstrate the following capabilities: Operating at pace and agile decision making - using evidence and applying judgement to balance pace, rigour and risk. Committed to delivering high-quality results, overcoming challenges, focusing on what matters, execution. Continuously looking for opportunities to learn, build skills and share learning. Sustaining energy and wellbeing Building strong relationships and collaboration, honest and open conversations. Budgeting and cost consciousness As a company driven by our values of Patient focus, Transparency, Respect and Integrity, we know inclusion and diversity are essential for us to be able to succeed. We want all our colleagues to thrive at GSK bringing their unique experiences, ensuring they feel good and to keep growing their careers. As a candidate for a role, we want you to feel the same way. As an Equal Opportunity Employer, we are open to all talent. In the US, we also adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to race/ethnicity, colour, national origin, religion, gender, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class ( US only). We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are. Please don't hesitate to contact us if you'd like to discuss any adjustments to our process which might help you demonstrate your strengths and capabilities. You can either call us on , or send an email As you apply, we will ask you to share some personal information which is entirely voluntary..... click apply for full job details
23/09/2022
Full time
Site Name: UK - Hertfordshire - Stevenage, USA - Connecticut - Hartford, USA - Delaware - Dover, USA - Maryland - Rockville, USA - Massachusetts - Cambridge, USA - Massachusetts - Waltham, USA - New Jersey - Trenton, USA - Pennsylvania - Upper Providence Posted Date: Jun 6 2022 The mission of the Data Science and Data Engineering (DSDE) organization within GSK Pharmaceuticals R&D is to get the right data, to the right people, at the right time. TheData Framework and Opsorganization ensures we can do this efficiently, reliably, transparently, and at scale through the creation of a leading-edge, cloud-native data services framework. We focus heavily on developer experience, on strong, semantic abstractions for the data ecosystem, on professional operations and aggressive automation, and on transparency of operations and cost. Achieving delivery of the right data to the right people at the right time needs design and implementation of data flows and data products which leverage internal and external data assets and tools to drive discovery and development is a key objective for the Data Science and Data Engineering (DSDE) team within GSK's Pharmaceutical R&D organization. There are five key drivers for this approach, which are closely aligned with GSK's corporate priorities of Innovation, Performance and Trust: Automation of end-to-end data flows :Faster and reliable ingestion of high throughput data in genetics, genomics and multi-omics, to extract value of investments in new technology (instrument to analysis-ready data in Enabling governance by design of external and internal data :with engineered practical solutions for controlled use and monitoring Innovative disease-specific and domain-expert specific data products : to enable computational scientists and their research unit collaborators to get faster to key insights leading to faster biopharmaceutical development cycles. Supporting e2ecode traceability and data provenance :Increasing assurance of data integrity through automation, integration. Improving engineering efficiency :Extensible, reusable, scalable,updateable,maintainable, virtualized traceable data and code would be driven by data engineering innovation and better resource utilization. We are looking for experienced Senior DevOps Engineers to join our growing Data Ops team. As a Senior Dev Ops Engineer is a highly technical individual contributor, building modern, cloud-native, DevOps-first systems for standardizing and templatizingbiomedical and scientificdata engineering, with demonstrable experience across the following areas: Deliver declarative components for common data ingestion, transformation and publishing techniques Define and implement data governance aligned to modern standards Establish scalable, automated processes for data engineering teams across GSK Thought leader and partner with wider DSDE data engineering teams to advise on implementation and best practices Cloud Infrastructure-as-Code Define Service and Flow orchestration Data as a configurable resource(including configuration-driven access to scientific data modelling tools) Observability (monitoring, alerting, logging, tracing, etc.) Enable quality engineering through KPIs and code coverage and quality checks Standardise GitOps/declarative software development lifecycle Audit as a service Senior DevOpsEngineers take full ownership of delivering high-performing, high-impactbiomedical and scientificdataopsproducts and services, froma description of apattern thatcustomer Data Engineers are trying touseall the way through tofinal delivery (and ongoing monitoring and operations)of a templated project and all associated automation. They arestandard-bearers for software engineering and quality coding practices within theteam andareexpected to mentor more junior engineers; they may even coordinate the work of more junior engineers on a large project.Theydevise useful metrics for ensuring their services are meeting customer demand and having animpact anditerate to deliver and improve on those metrics in an agile fashion. Successful Senior DevOpsEngineers are developing expertise with the types of data and types of tools that are leveraged in the biomedical and scientific data engineering space, andhas the following skills and experience(withsignificant depth in one or more of these areas): Demonstrable experience deploying robust modularised/container-based solutions to production (ideally GCP) and leveraging the Cloud NativeComputing Foundation (CNCF) ecosystem Significant depth in DevOps principles and tools (e.g.GitOps, Jenkins,CircleCI, Azure DevOps, etc.), and how to integrate these tools with other productivity tools (e.g. Jira, Slack, Microsoft Teams) to build a comprehensive workflow Programming in Python. Scala orGo Embedding agile software engineering (task/issue management, testing, documentation, software development lifecycle, source control, etc.) Leveraging major cloud providers, both via Kubernetesorvia vendor-specific services Authentication and Authorization flows and associated technologies (e.g.OAuth2 + JWT) Common distributed data tools (e.g.Spark, Hive) The DSDE team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career and development from day one. Why you? Basic Qualifications: We are looking for professionals with these required skills to achieve our goals: Masters in Computer Science with a focus in Data Engineering, DataOps, DevOps, MLOps, Software Engineering, etc, plus 5 years job experience (or PhD plus 3 years job experience) Experience with DevOps tools and concepts (e.g. Jira, GitLabs / Jenkins / CircleCI / Azure DevOps /etc.)Excellent with common distributed data tools in a production setting (Spark, Kafka, etc) Experience with specialized data architecture (e.g. optimizing physical layout for access patterns, including bloom filters, optimizing against self-describing formats such as ORC or Parquet, etc.) Experience with search / indexing systems (e.g. Elasticsearch) Expertise with agile development in Python, Scala, Go, and/or C++ Experience building reusable components on top of the CNCF ecosystem including Kubernetes Metrics-first mindset Experience mentoring junior engineers into deep technical expertise Preferred Qualifications: If you have the following characteristics, it would be a plus: Experience with agile software development Experience with building and designing a DevOps-first way of working Experience with building reusable components on top of the CNCF ecosystem including Kubernetes (or similar ecosystem ) LI-GSK Why GSK? Our values and expectationsare at the heart of everything we do and form an important part of our culture. These include Patient focus, Transparency, Respect, Integrity along with Courage, Accountability, Development, and Teamwork. As GSK focuses on our values and expectations and a culture of innovation, performance, and trust, the successful candidate will demonstrate the following capabilities: Operating at pace and agile decision making - using evidence and applying judgement to balance pace, rigour and risk. Committed to delivering high-quality results, overcoming challenges, focusing on what matters, execution. Continuously looking for opportunities to learn, build skills and share learning. Sustaining energy and wellbeing Building strong relationships and collaboration, honest and open conversations. Budgeting and cost consciousness As a company driven by our values of Patient focus, Transparency, Respect and Integrity, we know inclusion and diversity are essential for us to be able to succeed. We want all our colleagues to thrive at GSK bringing their unique experiences, ensuring they feel good and to keep growing their careers. As a candidate for a role, we want you to feel the same way. As an Equal Opportunity Employer, we are open to all talent. In the US, we also adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to race/ethnicity, colour, national origin, religion, gender, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class ( US only). We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are. Please don't hesitate to contact us if you'd like to discuss any adjustments to our process which might help you demonstrate your strengths and capabilities. You can either call us on , or send an email As you apply, we will ask you to share some personal information which is entirely voluntary..... click apply for full job details
Site Name: UK - Hertfordshire - Stevenage, USA - Connecticut - Hartford, USA - Delaware - Dover, USA - Maryland - Rockville, USA - Massachusetts - Waltham, USA - Pennsylvania - Upper Providence, Warren NJ Posted Date: Aug The mission of the Data Science and Data Engineering (DSDE) organization within GSK Pharmaceuticals R&D is to get the right data, to the right people, at the right time. TheData Framework and Opsorganization ensures we can do this efficiently, reliably, transparently, and at scale through the creation of a leading-edge, cloud-native data services framework. We focus heavily on developer experience, on strong, semantic abstractions for the data ecosystem, on professional operations and aggressive automation, and on transparency of operations and cost. Achieving delivery of the right data to the right people at the right time needs design and implementation of data flows and data products which leverage internal and external data assets and tools to drive discovery and development is a key objective for the Data Science and Data Engineering (DS D E) team within GSK's Pharmaceutical R&D organisation . There are five key drivers for this approach, which are closely aligned with GSK's corporate priorities of Innovation, Performance and Trust: Automation of end-to-end data flows: Faster and reliable ingestion of high throughput data in genetics, genomics and multi-omics, to extract value of investments in new technology (instrument to analysis-ready data in Enabling governance by design of external and internal data: with engineered practical solutions for controlled use and monitoring Innovative disease-specific and domain-expert specific data products : to enable computational scientists and their research unit collaborators to get faster to key insights leading to faster biopharmaceutical development cycles. Supporting e2 e code traceability and data provenance: Increasing assurance of data integrity through automation, integration Improving engineering efficiency: Extensible, reusable, scalable,updateable,maintainable, virtualized traceable data and code would b e driven by data engineering innovation and better resource utilization. We are looking for an experienced Sr. Data Ops Engineer to join our growing Data Ops team. As a Sr. Data Ops Engineer is a highly technical individual contributor, building modern, cloud-native, DevOps-first systems for standardizing and templatizingbiomedical and scientificdata engineering, with demonstrable experience across the following areas : Deliver declarative components for common data ingestion, transformation and publishing techniques Define and implement data governance aligned to modern standards Establish scalable, automated processes for data engineering team s across GSK Thought leader and partner with wider DSDE data engineering teams to advise on implementation and best practices Cloud Infrastructure-as-Code D efine Service and Flow orchestration Data as a configurable resource(including configuration-driven access to scientific data modelling tools) Ob servabilty (monitoring, alerting, logging, tracing, ...) Enable quality engineering through KPIs and c ode coverage and quality checks Standardise GitOps /declarative software development lifecycle Audit as a service Sr. DataOpsEngineerstake full ownership of delivering high-performing, high-impactbiomedical and scientificdataopsproducts and services, froma description of apattern thatcustomer Data Engineers are trying touseall the way through tofinal delivery (and ongoing monitoring and operations)of a templated project and all associated automation. They arestandard-bearers for software engineering and quality coding practices within theteam andareexpected to mentor more junior engineers; they may even coordinate the work of more junior engineers on a large project.Theydevise useful metrics for ensuring their services are meeting customer demand and having animpact anditerate to deliver and improve on those metrics in an agile fashion. A successfulSr.DataOpsEngineeris developing expertise with the types of data and types of tools that are leveraged in the biomedical and scientific data engineering space, andhas the following skills and experience(withsignificant depth in one or more of these areas): Demonstrable experience deploying robust modularised/ container based solutions to production (ideally GCP) and leveraging the Cloud NativeComputing Foundation (CNCF) ecosystem Significant depth in DevOps principles and tools ( e.g. GitOps , Jenkins, CircleCI , Azure DevOps, ...), and how to integrate these tools with other productivity tools (e.g. Jira, Slack, Microsoft Teams) to build a comprehensive workflow P rogramming in Python. Scala or Go Embedding agile s oftware engineering ( task/issue management, testing, documentation, software development lifecycle, source control, ) Leveraging major cloud providers, both via Kubernetes or via vendor-specific services Authentication and Authorization flows and associated technologies ( e.g. OAuth2 + JWT) Common distributed data tools ( e.g. Spark, Hive) The DSDE team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career and development from day one. Why you? Basic Qualifications: Bachelors degree in Computer Science with a focus in Data Engineering, DataOps, DevOps, MLOps, Software Engineering, etc, plus 7 years job experience or Masters degree with 5 Years of experience (or PhD plus 3 years job experience) Deep experience with DevOps tools and concepts ( e.g. Jira, GitLabs / Jenkins / CircleCI / Azure DevOps / ...) Excellent with common distributed data tools in a production setting (Spark, Kafka, etc) Experience with specialized data architecture ( e.g. optimizing physical layout for access patterns, including bloom filters, optimizing against self-describing formats such as ORC or Parquet, etc) Experience with search / indexing systems ( e.g. Elasticsearch) Deep expertise with agile development in Python, Scala, Go, and/or C++ Experience building reusable components on top of the CNCF ecosystem including Kubernetes Metrics-first mindset Experience mentoring junior engineers into deep technical expertise Preferred Qualifications: If you have the following characteristics, it would be a plus: Experience with agile software development Experience building and designing a DevOps-first way of working Demonstrated experience building reusable components on top of the CNCF ecosystem including Kubernetes (or similar ecosystem ) LI-GSK Why GSK? Our values and expectations are at the heart of everything we do and form an important part of our culture. These include Patient focus, Transparency, Respect, Integrity along with Courage, Accountability, Development, and Teamwork. As GSK focuses on our values and expectations and a culture of innovation, performance, and trust, the successful candidate will demonstrate the following capabilities: Operating at pace and agile decision making - using evidence and applying judgement to balance pace, rigour and risk. Committed to delivering high-quality results, overcoming challenges, focusing on what matters, execution. Continuously looking for opportunities to learn, build skills and share learning. Sustaining energy and wellbeing Building strong relationships and collaboration, honest and open conversations. Budgeting and cost consciousness As a company driven by our values of Patient focus, Transparency, Respect and Integrity, we know inclusion and diversity are essential for us to be able to succeed. We want all our colleagues to thrive at GSK bringing their unique experiences, ensuring they feel good and to keep growing their careers. As a candidate for a role, we want you to feel the same way. As an Equal Opportunity Employer, we are open to all talent. In the US, we also adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to neurodiversity, race/ethnicity, colour, national origin, religion, gender, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class ( US only). We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are. Please don't hesitate to contact us if you'd like to discuss any adjustments to our process which might help you demonstrate your strengths and capabilities. You can either call us on , or send an email As you apply, we will ask you to share some personal information which is entirely voluntary..... click apply for full job details
23/09/2022
Full time
Site Name: UK - Hertfordshire - Stevenage, USA - Connecticut - Hartford, USA - Delaware - Dover, USA - Maryland - Rockville, USA - Massachusetts - Waltham, USA - Pennsylvania - Upper Providence, Warren NJ Posted Date: Aug The mission of the Data Science and Data Engineering (DSDE) organization within GSK Pharmaceuticals R&D is to get the right data, to the right people, at the right time. TheData Framework and Opsorganization ensures we can do this efficiently, reliably, transparently, and at scale through the creation of a leading-edge, cloud-native data services framework. We focus heavily on developer experience, on strong, semantic abstractions for the data ecosystem, on professional operations and aggressive automation, and on transparency of operations and cost. Achieving delivery of the right data to the right people at the right time needs design and implementation of data flows and data products which leverage internal and external data assets and tools to drive discovery and development is a key objective for the Data Science and Data Engineering (DS D E) team within GSK's Pharmaceutical R&D organisation . There are five key drivers for this approach, which are closely aligned with GSK's corporate priorities of Innovation, Performance and Trust: Automation of end-to-end data flows: Faster and reliable ingestion of high throughput data in genetics, genomics and multi-omics, to extract value of investments in new technology (instrument to analysis-ready data in Enabling governance by design of external and internal data: with engineered practical solutions for controlled use and monitoring Innovative disease-specific and domain-expert specific data products : to enable computational scientists and their research unit collaborators to get faster to key insights leading to faster biopharmaceutical development cycles. Supporting e2 e code traceability and data provenance: Increasing assurance of data integrity through automation, integration Improving engineering efficiency: Extensible, reusable, scalable,updateable,maintainable, virtualized traceable data and code would b e driven by data engineering innovation and better resource utilization. We are looking for an experienced Sr. Data Ops Engineer to join our growing Data Ops team. As a Sr. Data Ops Engineer is a highly technical individual contributor, building modern, cloud-native, DevOps-first systems for standardizing and templatizingbiomedical and scientificdata engineering, with demonstrable experience across the following areas : Deliver declarative components for common data ingestion, transformation and publishing techniques Define and implement data governance aligned to modern standards Establish scalable, automated processes for data engineering team s across GSK Thought leader and partner with wider DSDE data engineering teams to advise on implementation and best practices Cloud Infrastructure-as-Code D efine Service and Flow orchestration Data as a configurable resource(including configuration-driven access to scientific data modelling tools) Ob servabilty (monitoring, alerting, logging, tracing, ...) Enable quality engineering through KPIs and c ode coverage and quality checks Standardise GitOps /declarative software development lifecycle Audit as a service Sr. DataOpsEngineerstake full ownership of delivering high-performing, high-impactbiomedical and scientificdataopsproducts and services, froma description of apattern thatcustomer Data Engineers are trying touseall the way through tofinal delivery (and ongoing monitoring and operations)of a templated project and all associated automation. They arestandard-bearers for software engineering and quality coding practices within theteam andareexpected to mentor more junior engineers; they may even coordinate the work of more junior engineers on a large project.Theydevise useful metrics for ensuring their services are meeting customer demand and having animpact anditerate to deliver and improve on those metrics in an agile fashion. A successfulSr.DataOpsEngineeris developing expertise with the types of data and types of tools that are leveraged in the biomedical and scientific data engineering space, andhas the following skills and experience(withsignificant depth in one or more of these areas): Demonstrable experience deploying robust modularised/ container based solutions to production (ideally GCP) and leveraging the Cloud NativeComputing Foundation (CNCF) ecosystem Significant depth in DevOps principles and tools ( e.g. GitOps , Jenkins, CircleCI , Azure DevOps, ...), and how to integrate these tools with other productivity tools (e.g. Jira, Slack, Microsoft Teams) to build a comprehensive workflow P rogramming in Python. Scala or Go Embedding agile s oftware engineering ( task/issue management, testing, documentation, software development lifecycle, source control, ) Leveraging major cloud providers, both via Kubernetes or via vendor-specific services Authentication and Authorization flows and associated technologies ( e.g. OAuth2 + JWT) Common distributed data tools ( e.g. Spark, Hive) The DSDE team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career and development from day one. Why you? Basic Qualifications: Bachelors degree in Computer Science with a focus in Data Engineering, DataOps, DevOps, MLOps, Software Engineering, etc, plus 7 years job experience or Masters degree with 5 Years of experience (or PhD plus 3 years job experience) Deep experience with DevOps tools and concepts ( e.g. Jira, GitLabs / Jenkins / CircleCI / Azure DevOps / ...) Excellent with common distributed data tools in a production setting (Spark, Kafka, etc) Experience with specialized data architecture ( e.g. optimizing physical layout for access patterns, including bloom filters, optimizing against self-describing formats such as ORC or Parquet, etc) Experience with search / indexing systems ( e.g. Elasticsearch) Deep expertise with agile development in Python, Scala, Go, and/or C++ Experience building reusable components on top of the CNCF ecosystem including Kubernetes Metrics-first mindset Experience mentoring junior engineers into deep technical expertise Preferred Qualifications: If you have the following characteristics, it would be a plus: Experience with agile software development Experience building and designing a DevOps-first way of working Demonstrated experience building reusable components on top of the CNCF ecosystem including Kubernetes (or similar ecosystem ) LI-GSK Why GSK? Our values and expectations are at the heart of everything we do and form an important part of our culture. These include Patient focus, Transparency, Respect, Integrity along with Courage, Accountability, Development, and Teamwork. As GSK focuses on our values and expectations and a culture of innovation, performance, and trust, the successful candidate will demonstrate the following capabilities: Operating at pace and agile decision making - using evidence and applying judgement to balance pace, rigour and risk. Committed to delivering high-quality results, overcoming challenges, focusing on what matters, execution. Continuously looking for opportunities to learn, build skills and share learning. Sustaining energy and wellbeing Building strong relationships and collaboration, honest and open conversations. Budgeting and cost consciousness As a company driven by our values of Patient focus, Transparency, Respect and Integrity, we know inclusion and diversity are essential for us to be able to succeed. We want all our colleagues to thrive at GSK bringing their unique experiences, ensuring they feel good and to keep growing their careers. As a candidate for a role, we want you to feel the same way. As an Equal Opportunity Employer, we are open to all talent. In the US, we also adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to neurodiversity, race/ethnicity, colour, national origin, religion, gender, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class ( US only). We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are. Please don't hesitate to contact us if you'd like to discuss any adjustments to our process which might help you demonstrate your strengths and capabilities. You can either call us on , or send an email As you apply, we will ask you to share some personal information which is entirely voluntary..... click apply for full job details
Job description We currently have an opportunity for an Enterprise Data Architect to join our IT team in London. The Enterprise Data Architect will ensure A&O has focus on and maintains an enterprise data governance framework for data policies, standards, process and practices, across A&O, to achieve the required level of consistency and quality to meet A&O business needs. The role will be the custodian of data, setting the vision for A&O's use of data and will manage A&Os data catalogue to improve the quality and value of core data assets, respond to regulatory requirements as well as support strategic functional requirements. The role will manage the way that people and programs engage with data, ensuring that data can be turned into valuable insights that inform business decisions. The role holder will consistently communicate the business benefit of data standards and will champion and govern those standards across the firm. The role holder will ensure internal procedures keep pace with evolving data regulation and compliance. Role and responsibilities Manage and govern a unified view of A&O data, its data linage and provenance Govern and manage the A&O data catalogue across all data assets. Ensure data is discoverable, well understood, and trusted Drive innovation and growth through the use of data, unlocking data for insightful business decisions Help establish best practice, rules and ownership of A&Os taxonomy and ontology Build and maintain good working-relationships across A&Os Data Stewards to ensure internal stakeholders and leaders are informed and aligned Create a Data Governance and Quality function, including processes and tools to achieve A&Os data objectives Define a proactive approach to the management of data models, definitions, data governance, ethics and data processing rules to provide timely, appropriate, accurate and up-to-date information at the point of need Actively use the trends in data quality and data governance to drive positive change in people, process, technology and governance Develop and be responsible for the standards, policies and procedures for the on-going implementation of data governance Ensure alignment between data governance best practice, Data Privacy procedures and requirements and the IT Information Security strategy Work closely with and set direction for the Trusted Data Platform team, staying close to opportunities and challenges that exist within A&O, provide guidance on new products, approaches and supplier relationships that could impact data collection, processing and analytics Key requirements Business Competencies Aptitude for and experience of creating, managing, motivating and developing teams Commercial acumen including an understanding of the overall picture of how the IT service costs and value add to the business Excellent communication, interpersonal and influencing skills, including the ability to communicate both on technical and business levels. Excellent customer-facing skills with a good grasp of key drivers and requirements within the Business. High level of personal credibility, impact and influence with proven ability to work effectively and persuasively at all levels of the business Knowledge & Experience Knowledge and awareness of business and technology issues related to the management of enterprise wide data Expert level data modelling experience. Including a deep understanding of relational, taxonomical and ontological modelling approaches Strong recent experience of developing and managing an enterprise data catalogue Proven experience of developing and implementing a Data Governance Framework and a Data Quality Management service Keen eye for detail with a genuine interest in understanding the journey data takes throughout A&O Demonstrable experience in building, delivering and managing detailed data quality measurement frameworks Comfortable presenting complex data models, flows and relationships to non-data peers and colleagues An expert in information management practices including information lifecycle management, data profiling, master data management, data audits and requirements gathering Clear knowledge and experience relating to the application of data governance, data privacy and data ethics principles to support and drive data strategy Evidence of establishing governance processes, with engaged teams, leading and implementing enterprise-wide data governance and demonstrable improvements in data quality Preferable: Knowledge and experience relating to MLOps, testing and quality management Preferable: Experienced in managing, versioning and automating data and systems Preferable: Experience of unstructured and semi-structured data and associated processing approaches. NLP and Machine learning experience a distinct advantage. Preferable: Experienced at using relevant frameworks such as GDPR and other data privacy regulations to drive data governance ethics Preferable: Experience using automated approaches to manage and support data privacy compliance Is a collaborative team player fostering strong working relationships, with strong culture awareness Strong leadership and influencing skills; interacting with senior stakeholders; highly personable Strong ability to extract information by questioning, active listening and interviewing Results orientated to ensure change and delivery project metrics are meaningful and supported with robust business data Analytical with strong numeracy and good statistical skills Experience of working in Agile project environments Ability to work with technical, (developers, data engineers, data scientists) and nontechnical staff Allen & Overy LLP is committed to being an inclusive employer and we are happy to consider flexible working arrangements. Additional information - External It's Time Allen & Overy is a leading global law firm operating in over thirty countries. By turning our insight, technology and talent into ground-breaking solutions, we've earned a place at the forefront of our industry. Our lawyers are leaders in their field - and the same goes for our support teams. Ambitious, driven and open to fresh perspectives, we find innovative new ways to deliver our services and maintain our reputation for excellence, in all that we do. The nature of law is changing and with that change brings unique opportunities. With our collaborative working culture, flexibility, and a commitment to your progress, we build rewarding careers. By joining our global team, you are supported by colleagues from around the world. If you're ready for a new challenge, it's time to seize the opportunity.
15/09/2021
Full time
Job description We currently have an opportunity for an Enterprise Data Architect to join our IT team in London. The Enterprise Data Architect will ensure A&O has focus on and maintains an enterprise data governance framework for data policies, standards, process and practices, across A&O, to achieve the required level of consistency and quality to meet A&O business needs. The role will be the custodian of data, setting the vision for A&O's use of data and will manage A&Os data catalogue to improve the quality and value of core data assets, respond to regulatory requirements as well as support strategic functional requirements. The role will manage the way that people and programs engage with data, ensuring that data can be turned into valuable insights that inform business decisions. The role holder will consistently communicate the business benefit of data standards and will champion and govern those standards across the firm. The role holder will ensure internal procedures keep pace with evolving data regulation and compliance. Role and responsibilities Manage and govern a unified view of A&O data, its data linage and provenance Govern and manage the A&O data catalogue across all data assets. Ensure data is discoverable, well understood, and trusted Drive innovation and growth through the use of data, unlocking data for insightful business decisions Help establish best practice, rules and ownership of A&Os taxonomy and ontology Build and maintain good working-relationships across A&Os Data Stewards to ensure internal stakeholders and leaders are informed and aligned Create a Data Governance and Quality function, including processes and tools to achieve A&Os data objectives Define a proactive approach to the management of data models, definitions, data governance, ethics and data processing rules to provide timely, appropriate, accurate and up-to-date information at the point of need Actively use the trends in data quality and data governance to drive positive change in people, process, technology and governance Develop and be responsible for the standards, policies and procedures for the on-going implementation of data governance Ensure alignment between data governance best practice, Data Privacy procedures and requirements and the IT Information Security strategy Work closely with and set direction for the Trusted Data Platform team, staying close to opportunities and challenges that exist within A&O, provide guidance on new products, approaches and supplier relationships that could impact data collection, processing and analytics Key requirements Business Competencies Aptitude for and experience of creating, managing, motivating and developing teams Commercial acumen including an understanding of the overall picture of how the IT service costs and value add to the business Excellent communication, interpersonal and influencing skills, including the ability to communicate both on technical and business levels. Excellent customer-facing skills with a good grasp of key drivers and requirements within the Business. High level of personal credibility, impact and influence with proven ability to work effectively and persuasively at all levels of the business Knowledge & Experience Knowledge and awareness of business and technology issues related to the management of enterprise wide data Expert level data modelling experience. Including a deep understanding of relational, taxonomical and ontological modelling approaches Strong recent experience of developing and managing an enterprise data catalogue Proven experience of developing and implementing a Data Governance Framework and a Data Quality Management service Keen eye for detail with a genuine interest in understanding the journey data takes throughout A&O Demonstrable experience in building, delivering and managing detailed data quality measurement frameworks Comfortable presenting complex data models, flows and relationships to non-data peers and colleagues An expert in information management practices including information lifecycle management, data profiling, master data management, data audits and requirements gathering Clear knowledge and experience relating to the application of data governance, data privacy and data ethics principles to support and drive data strategy Evidence of establishing governance processes, with engaged teams, leading and implementing enterprise-wide data governance and demonstrable improvements in data quality Preferable: Knowledge and experience relating to MLOps, testing and quality management Preferable: Experienced in managing, versioning and automating data and systems Preferable: Experience of unstructured and semi-structured data and associated processing approaches. NLP and Machine learning experience a distinct advantage. Preferable: Experienced at using relevant frameworks such as GDPR and other data privacy regulations to drive data governance ethics Preferable: Experience using automated approaches to manage and support data privacy compliance Is a collaborative team player fostering strong working relationships, with strong culture awareness Strong leadership and influencing skills; interacting with senior stakeholders; highly personable Strong ability to extract information by questioning, active listening and interviewing Results orientated to ensure change and delivery project metrics are meaningful and supported with robust business data Analytical with strong numeracy and good statistical skills Experience of working in Agile project environments Ability to work with technical, (developers, data engineers, data scientists) and nontechnical staff Allen & Overy LLP is committed to being an inclusive employer and we are happy to consider flexible working arrangements. Additional information - External It's Time Allen & Overy is a leading global law firm operating in over thirty countries. By turning our insight, technology and talent into ground-breaking solutions, we've earned a place at the forefront of our industry. Our lawyers are leaders in their field - and the same goes for our support teams. Ambitious, driven and open to fresh perspectives, we find innovative new ways to deliver our services and maintain our reputation for excellence, in all that we do. The nature of law is changing and with that change brings unique opportunities. With our collaborative working culture, flexibility, and a commitment to your progress, we build rewarding careers. By joining our global team, you are supported by colleagues from around the world. If you're ready for a new challenge, it's time to seize the opportunity.
