276 to 300 of 301 MLOps Jobs in England

will design, develop, and deploy AI solutions across secure environments, building end-to-end ML pipelines, RAG components, and scalable data processing. Responsibilities include MLOps, architecture decisions, and collaborating with cross-functional teams to deliver production-ready AI systems with strong emphasis on security and compliance. #J-18808-Ljbffr ...

This hybrid role involves leading the design of ML platforms and infrastructure, ensuring effective deployment and monitoring of models. The ideal candidate has extensive MLOps experience, strong software engineering skills, and familiarity with cloud platforms such as GCP. Join a diverse team at iProov, working at the intersection of technology ...

Architect for AI who will own end-to-end delivery of AI/ML engagements, from silicon and data center design to software and MLOps governance. This hands-on role spans GPU infrastructure, high-performance networking, model training, and responsible AI frameworks. The candidate will lead technical delivery teams, chair ...

will own the end-to-end lifecycle of models, ensure decisions are safe and explainable, and lead a multi-disciplinary DS/ML/MLOps team with strong governance and risk controls. #J-18808-Ljbffr ...

Lead MLOps Engineer (Contract) We’re supporting a leading UK heritage brand on the appointment of a Lead MLOps Engineer (Contractor) to help scale and optimise their machine learning platform capabilities. You’ll play a key role in designing and enhancing enterprise MLOps infrastructure, enabling data science teams to rapidly … programme at a pivotal stage and help shape the future AI and machine learning landscape across the business. Key Skills/experience Strong commercial MLOps engineering experience at Senior/Lead level Cloud platform experience: GCP essential, Azure nice to have Experienced operating in large scale complex data environments Large ...

Lead to drive production-grade models and automated decisioning for the Economic Crime Hub. You will own end-to-end model lifecycle, overseeing MLOps, governance, and scale across the business, partnering with Analytics, Product, and Technology teams. You will build and lead a multidisciplinary DS/ML/MLOps function ...

low. Join us on our journey... Let’s create something awesome, together, today. About the role and team: We are looking for a Lead MLOps Developer to own the design and delivery of a production-grade machine learning platform on AWS. What you’ll be doing Design and maintain … production MLOps platform on Amazon SageMaker (Studio, Training, Pipelines, Endpoints) — including model registry, automated retraining, drift monitoring, and governance gates Lead the migration of a 12-model production suite (e.g., the CVM suite) from legacy infrastructure to SageMaker, owning parity testing methodology and sign-off Build and maintain CI/ ...

low. Join us on our journey... Let’s create something awesome, together, today. About the role and team: We are looking for a Lead MLOps Developer to own the design and delivery of a production-grade machine learning platform on AWS. What you’ll be doing Design and maintain … production MLOps platform on Amazon SageMaker (Studio, Training, Pipelines, Endpoints) — including model registry, automated retraining, drift monitoring, and governance gates Lead the migration of a 12-model production suite (e.g., the CVM suite) from legacy infrastructure to SageMaker, owning parity testing methodology and sign-off Build and maintain CI/ ...

design, deployment, integration and continuous improvement of enterprise AI and machine learning capabilities, including ML platforms, generative AI, LLM services, feature pipelines and MLOps tooling. The role is responsible for establishing AI engineering standards, governance and best practices across the model lifecycle, ensuring solutions are scalable, secure, compliant and deliver … measurable business value. About the role Lead AI engineering, MLOps and platform teams, driving high-quality delivery and operational excellence. Define and maintain engineering standards, AI guardrails and Responsible AI practices. Oversee model development, deployment, monitoring, evaluation and continuous improvement processes. Drive preventative controls, automation, observability and root cause analysis ...

engineering teams Developing and deploying AI/ML features into live products Implementing anomaly detection or predictive analytics on structured operational data Managing MLOps including deployment pipelines, model monitoring, and retraining Designing REST APIs and integrating MCP patterns Contributing to a structured product roadmap Job Requirements: Experience in software engineering … anomaly detection or predictive analytics Proficiency in Python and TypeScript/JavaScript Experience with REST API design and MCP integration patterns Knowledge of MLOps practices Understanding of graph-based dependency or impact analysis (desirable) Experience with AI features in compliance or governance contexts (desirable) Familiarity with SAP BTP (desirable) Benefits ...

design, deployment, integration and continuous improvement of enterprise AI and machine learning capabilities, including ML platforms, generative AI, LLM services, feature pipelines and MLOps tooling. The role is responsible for establishing AI engineering standards, governance and best practices across the model lifecycle, ensuring solutions are scalable, secure, compliant and deliver … measurable business value. About the role Lead AI engineering, MLOps and platform teams, driving high‐quality delivery and operational excellence. Define and maintain engineering standards, AI guardrails and Responsible AI practices. Oversee model development, deployment, monitoring, evaluation and continuous improvement processes. Drive preventative controls, automation, observability and root‐cause analysis ...

generative experiences. Set technical direction, establishing high standards for modelling approaches, evaluation, deployment, and monitoring. Collaborate closely with Product, Engineering, Data Science, and MLOps to ensure seamless deployment and scalability of ML models. Build and lead a high-performing team of approximately six Machine Learning Scientists, fostering their professional growth … implement scalable, maintainable ML practices. Manage and develop a team of skilled ML scientists, fostering technical expertise and leadership. Work closely with Engineering and MLOps teams to ensure models are effectively deployed, monitored, and scaled. Communicate the value and impact of ML & AI initiatives to senior stakeholders, influencing strategic decisions. ...

accuracy, and consistency of training data across multiple concurrent projects and robot platforms. Collaborate with machine learning teams to shape the Capability Factory, streamline MLOps, and build the evaluation workflows that close the loop between training runs and real‐world robot performance. Build data warehouse solutions and BI dashboards that … progress, and operational health. Establish and uphold best practices for data management – versioning, access control, security, and compliance. Nice to Have ML infrastructure or MLOps experience – understanding of how training jobs run, how model artifacts are managed, and what makes an evaluation pipeline trustworthy; you’ve worked alongside or directly ...

Fosse-1 is seeking a Lead MLOps Engineer (Contract) to scale and optimise an enterprise ML platform for a leading UK heritage brand. You will design and enhance MLOps infrastructure to enable data science teams to deploy, monitor and manage models in production. This senior role requires leadership ...

Protection and Legal, covering model risk, data privacy, transparency, human in the loop and auditing. Build the target operating model for AI engineering and MLOps, including model lifecycle management, monitoring, incident response, versioning and cost/performance optimisation. Set global standards for AI platforms, toolchains and integration patterns; ensure interoperability … grasp of responsible AI, security and compliance, including model risk management, privacy, data residency, human oversight and auditability. Hands on understanding of AI/MLOps practices and platforms, including model lifecycle, observability, cost control, CI/CD, feature stores and data integration. Experience defining and governing enterprise standards and architectures ...

The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We’re in the heart of the UK government with ...

Ready to shape the future of work? At Genpact, we don’t just adapt to change—we drive it. AI and digital innovation are redefining industries, and we’re leading the charge. Genpact’s AI ...

Machine Learning Engineer, key skills: Strong hands-on experience with Snowflake ML Python expertise - Scikit-Learn, TensorFlow, Pytorch etc Strong understanding of model deployment MLOps - experienced in designing and implementing MLOps frameworks and best practices Strong stakeholder management AWS Sagemaker is a nice to have Experience with feature stores, model … registries and ML obserability tooling Machine Learning Engineer, Snowflake ML, Python, MLOps, Sagemaker Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built, and we welcome applications from people of all backgrounds and perspectives. Our success is driven ...

Role Highlights: Position: Machine Learning Engineer (MLOps Lead) Location: London, UK Contract: 6 months (extendable) Tech Focus: GCP (Vertex AI – essential), Python, APIs, CI/CD, Docker Key Skills Required :Strong MLOps/ML Engineering experience (5+ years )Hands-on experience with GCP (Vertex AI )Excellent Python development skill sExperience ...

capabilities including LLM-powered and generative experiences Setting technical direction across modelling, evaluation and ML lifecycle management Partnering closely with Product, Engineering and MLOps teams Improving scalability, observability and speed-to-production across ML systems Leading and developing a high-performing team of ML specialists and leaders Acting … interest in LLMs, generative AI and AI-powered customer experiences Excellent stakeholder management and communication skills Strong cross-functional collaboration across Product, Engineering and MLOps Why This Role? Opportunity to define the future of ML & AI within a major consumer platform High visibility and influence across Product, Technology and Commercial ...

roadmap and prioritise high-impact initiatives Set technical direction across modelling approaches, feature design and evaluation frameworks Work closely with Engineering and MLOps teams to ensure ML systems are production-ready, scalable and well-supported Act as the central ML authority within PDT, aligning teams around best practices and shared … communication skills with the ability to translate technical concepts into business value Experience working cross-functionally with Product, Engineering and platform teams such as MLOps Track record of influencing senior stakeholders and driving alignment across teams What's in it for you Competitive Pay & Bonuses: Plus, generous pension plans & staff ...

lifecycle of models and AI agents Collaborate with Analytics, Product, and Technology teams Establish and enforce standards for model development and MLOps Build and lead a multi-disciplinary Data Science capability Requirements Extensive experience leading engineering-grade Data Science and AI capabilities Proven track record of designing and deploying … foster high-performing teams Experience within financial crime or fraud environments preferred Deep expertise in model development and lifecycle management Strong knowledge of MLOps, model monitoring, and production systems Experience working within regulated environments Core Competencies Demonstrates extensive experience in leading Data Science and AI capabilities, with a strong focus ...

technical progression of team members. Qualifications Extensive experience designing, building, and deploying production-grade AI and ML solutions, with strong understanding of ML engineering, MLOps, and model lifecycle management. Proven track record of developing AI platforms and deployment capabilities that support secure, reliable, and efficient delivery of AI solutions. Ability … systems. Deep expertise in ML engineering and model lifecycle management, including deployment, monitoring, optimisation, and ongoing performance management. Strong knowledge of MLOps practices, including CI/CD, pipeline orchestration, automation, and production model management. Proven ability to translate analytical models and decision strategies into robust, operational decisioning systems. Experience developing ...

Overview 🚀 Director of Cloud Transformation | London (Hybrid) We're looking for a senior, commercially astute cloud leader to define and champion a market-leading cloud transformation and innovation agenda . This is a high-impact ...

Cloud is seeking a Forward Deployed Engineer to lead the end-to-end delivery of conversational AI pilots at client sites. You will transform rapid prototypes into scalable, secure AI systems, working across software engineering ...