15 of 15 Permanent MLOps Jobs in Oxfordshire

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 ...

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 ...

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. ...

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 ...

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 ...

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 Private Medical Insurance Dental Insurance Parental Support Salary‐Exchange Pension Employee Assistance Programme (EAP) Local Oxford Discounts Cycle‐to‐work ...

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 ...

proof-of-concepts, pilots and production implementations.Collaborate with Agile delivery teams to embed AI capabilities into products and services.Establish CI/CD pipelines and MLOps practices.Drive technical quality, performance and operational resilience.Generative AI & Large Language ModelsDesign and implement solutions using Large Language Models (LLMs).Develop Retrieval-Augmented Generation (RAG) architectures.Implement … AI.Experience with Python and modern development frameworks.Strong understanding of APIs, microservices and cloud-native architecture.Experience with data platforms, databases and data engineering concepts.Knowledge of MLOps, DevOps and CI/CD practices.AI & DataHands-on experience with:Large Language Models (LLMs)Prompt engineeringRetrieval-Augmented Generation (RAG)Vector databasesAI orchestration frameworks such ...

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 ...

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 ...

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 ...

Lumai Limited is building a breakthrough AI accelerator for data centers using 3D optical compute. We seek a senior MLOps Engineer to own end-to-end ML pipelines, tooling, and production deployments for models from research to silicon-validated production. In this high-ownership role, you’ll collaborate with ...