1 to 25 of 27 MLOps Jobs in the Thames Valley

generative AI and the modern AI stack, including large language models, prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation/monitoring and MLOps principles, with the ability to shape investment cases and operating models at scale.Extensive experience providing executive oversight for production AI delivery (you steer architecture and engineering ...

technical stakeholders. Desirable Experience The following would be advantageous: Multimodal AI and reasoning. Edge or offline AI deployments. Kubernetes, particularly EKS or OpenShift. MLOps, including model evaluation, monitoring and reproducibility. Observability for agentic AI systems, including model performance, agent behaviour and drift. Agent orchestration and inter-agent communication protocols such ...

Skills:Professional certifications in AWS, Azure, GCP, or Data Engineering.Experience within aerospace, defence, manufacturing, or highly regulated industries.Knowledge of AI/ML platforms and MLOps practices.Experience with graph databases and knowledge engineering solutions.Experience implementing data mesh or data fabric architectures.Enterprise Architecture experience.Experience leading large-scale data modernisation programmes.Knowledge of defence ...

certifications in AWS, Azure, GCP, or Data Engineering. Experience within aerospace, defence, manufacturing, or highly regulated industries. Knowledge of AI/ML platforms and MLOps practices. Experience with graph databases and knowledge engineering solutions. Experience implementing data mesh or data fabric architectures. Enterprise Architecture experience. Experience leading large-scale data ...

data‐driven systems in production or near‐production settings. Experience with generative AI systems, LLM‐enabled applications or evaluation pipelines. Experience with cloud platforms, MLOps tooling, model serving or platform engineering. Advanced use of Linux, Docker, version control, CI/CD and service‐oriented deployment practices. Experience working across ...

advanced AI, and specifically: The management of people, process, documentation associated with the development, deployment, maintenance, training and operational management of Machine Learning solutions (MLOps) The management of people, process, documentation, maintenance and operational management of Generative AI solutions (GenAIOps/LLMOps) Manage, objectively assess and track Technology Readiness Levels ...

writing clean, efficient, and modular code suitable for production environments. Desirable Skills or Knowledge Familiarity with AMO physics or quantum machine learning. Experience with MLOps best practices. Knowledge of systems like Apache Kafka, MQTT or real‐time data pipelines. Experience with cloud platforms (AWS, Azure, GCP). Deep expertise ...

cost management Model serving and inference at production scale (eg KServe, RayServe, Triton, vLLM, or similar) with real latency and cost constraints(preferred RayServe) MLOps pipeline tooling - training pipelines, model registries, feature stores, and lineage (Kubeflow, MLflow, Feast, Weights & Biases, or equivalents) LLMOps in production - inference serving, prompt/version ...

enterprise and industry-standard software platforms. A strong understanding of infrastructure security, reliability and operational best practice. Desirable Experience The following would be advantageous: MLOps or LLMOps experience. Experience with platforms such as SageMaker, Kubeflow or ZenML . Extensive on-premises Kubernetes deployment experience. Prometheus or comparable observability platforms. ...

right level of review and controls based on riskCollaborate with Cloud, Data, Networks, and Digital teams to ensure secure configuration of AI infrastructure, including MLOps and compute environmentsGuide programmes and product teams with clear, practical recommendations that balance security, delivery, and innovationDrive compliance with regulatory, legal, and internal frameworks (including ...

Preferred Experience with multimodal reasoning Experience with edge or offline AI deployments Familiarity with Kubernetes (EKS/OpenShift) for monitoring and managing deployed applications MLOps experience - model evaluation, monitoring, reproducibility Observability tooling for agentic systems (model drift, agent behaviour, performance monitoring) Experience with agent orchestration patterns and inter‐agent communication ...

infrastructure Desirable attributes: Hands‐on experience building LLM‐based systems Experience testing non‐deterministic systems Understanding of statistics and inferential methods LangGraph, RAG, MCP, MLOps, IaaC, AWS What we offer Some of the benefits we include are: Private Medical Insurance Dental Insurance Parental Support Salary‐Exchange Pension Employee Assistance Programme ...

Senior MLOps & Data EngineerLocation: Oxford Based (Hybrid)Type: PermanentSalary: 90,000 - 120,000 + Bonus + Equity + BenefitsThe Opportunity We're supporting an innovative biotechnology organisation that is investing heavily in the next generation of data, machine learning and scientific computing capabilities.As part of a growing technology team … workflow automation and machine learning operations. You will help transform research and analytical workflows into reliable, secure and scalable production systems.ResponsibilitiesDesign and build scalable MLOps infrastructure to support model deployment, monitoring, retraining and lifecycle management.Productionise machine learning and scientific computing workflows using Python, container technologies and modern software engineering practices.Develop ...

Senior MLOps & Data EngineerLocation: Oxford Based (Hybrid)Type: PermanentSalary: 90,000 - 120,000 + Bonus + Equity + BenefitsThe Opportunity We're supporting an innovative biotechnology organisation that is investing heavily in the next generation of data, machine learning and scientific computing capabilities. As part of a growing technology team … automation and machine learning operations. You will help transform research and analytical workflows into reliable, secure and scalable production systems. ResponsibilitiesDesign and build scalable MLOps infrastructure to support model deployment, monitoring, retraining and lifecycle management. Productionise machine learning and scientific computing workflows using Python, container technologies and modern software engineering ...

technical delivery while also leading multiple projects or workstreams in parallel. Desirable • Experience establishing or embedding best practice in ML engineering, software delivery or MLOps within a team or function. • Experience in regulated, enterprise or operationally complex environments. • Experience promoting reuse through shared frameworks, tooling, templates or engineering standards. • Experience ...

designs and ensure strong technical architecture.Drive the transition from experimental AI capabilities to scalable production systems.What We Are Looking ForStrong engineering background (ML engineering, MLOps engineer, or equivalent).Proven experience building complex systems from 01.Ability to independently write production-quality code and build functional prototypes.Practical experience with LLM application architectures ...

ensure strong technical architecture. Drive the transition from experimental AI capabilities to scalable production systems. What We Are Looking ForStrong engineering background (ML engineering, MLOps engineer, or equivalent).Proven experience building complex systems from 01.Ability to independently write production-quality code and build functional prototypes. Practical experience with LLM application ...

Earth‐system or environmental services, Copernicus, Destination Earth or machine‐learning‐enabled forecasting workflows, including relevant approaches to reproducibility, model versioning, workflow orchestration or MLOps Languages Candidates must be able to work effectively in English. A good knowledge of one of the Centre’s other working languages (French or German ...

CODAS project and related initiatives at AND-E Lab. Ideal candidates have 5+ years in ML/AI, strong Python, cloud/MLOps experience, and a collaborative mindset to work with partners and stakeholders across experiments and #J-18808-Ljbffr ...

every project. Strong communication skills: you'll need to challenge stakeholder expectations sometimes, not just relay them. Bonus points: experience establishing ML engineering/MLOps best practice from scratch, background in regulated or enterprise environments, or a track record of driving reuse through shared frameworks and tooling. Why join ...

Customer Analytics, Marketing Analytics, Customer Lifetime Value, Churn Prediction, Demand Forecasting, Stock Forecasting, Production Machine Learning, Cloud Data Platforms, Data Products, Git, Version Control, MLOps, Data Pipelines. Location: Hybrid role. 2 days per week in office Either: Welwyn Garden City, Hertfordshire or Slough, Berkshire Type: Permanent | Full-Time Overview: @mecscomms … Data integration & modelling * Stakeholder management * Agile delivery experience Desirable: * MLflow * PyTorch * Databricks Asset Bundles * Graph Databases * Azure Machine Learning * GitHub Actions * CI/CD * MLOps * Marketing Analytics * Customer Lifetime Value (CLV) * Churn Prediction * Retail Analytics * Customer Personalisation * Decision Intelligence Key Traits: * Curious & analytical * Commercially minded * Customer focused * Strong statistical thinking ...

currently available globally. The Role We are building custom AI hardware and the full-stack software ecosystem to run it. As our first dedicated MLOps Engineer, you will own the infrastructure that takes models from research to silicon-validated production — designing, building, and operating the pipelines, tooling, and platforms that ...

acceleration platform that enables complex workloads to run faster, more efficiently, and at significantly lower cost than traditional approaches.This is an opportunity for an MLOps Engineer to join a highly talented team to develop a breakthrough computing platform with the potential to transform large-scale AI deployment.What they're looking … MLOps experience- building and maintaining production ML pipelines ML infrastructure expertise- experiment tracking, model management, and deployment Strong Python skills- experience with PyTorch, JAX, or similar frameworks Platform engineering- Docker, Kubernetes, Slurm, and distributed systems CI/CD knowledge- automating testing, validation, and deployments Performance optimisation- profiling and benchmarking ...

reliable, well-monitored, cost-effective models in production - deployment, retraining, monitoring and governance - and the service levels (SLAs) of the ML organization. Partnering with MLOps infrastructure team.Partner across the company. Translate commercial strategy into an ML roadmap with Product, Engineering, Design, and Analytics leadership; represent ML in executive planning … partners across Product and Engineering and shaping strategy, not just execution.A strategic player-coach's technical depth: current enough in modern ML, experimentation, and MLOps to set direction, review architecture, and hold the scientific bar.Strong grounding in experimentation and statistics — A/B testing, causal inference, and rigorous measurement ...

other in Kuala Lumpur, Malaysia. With this role, you will be accountable for the reliable, secure and efficient operation of the organisation’s MLOps platform and Machine Learning Operations (MLOps) capabilities.In this role you will report to the Head of Data Platform and Services, the role ensures platform services meet … risk management and compliance for production data and AI services.Key ResponsibilitiesOwn and manage the day-to-day operation of the Databricks Lakehouse Platform and MLOps services, ensuring high availability, performance, security, and user satisfaction. Lead platform service management activities, including incident, problem, change, and request processes, while coordinating support ...