1 to 25 of 32 MLOps Jobs in the Thames Valley

scaling tech company with clear progression opportunities. Collaborative culture: A dynamic team that values innovation, experimentation, and learning. Cutting-edge tools: Access to modern data platforms, cloud infrastructure, and MLOps frameworks. Competitive package: Salary, bonus, and flexible benefits. If you’re a driven Data Scientist ready to shape the future of technology and software innovation, we’d love to hear More ❯

Familiarity with deep learning frameworks (e.g. PyTorch, TensorFlow). Exposure to cloud platforms (AWS, GCP, or Azure). Experience with experimental design, research methods, or academic publishing. Understanding of MLOps, version control (Git), or containerisation (e.g. Docker). Benefits: 💰 Competitive Salary & Bonus: £35,000 – £45,000 plus bonus 🏢 Central London Office: Modern workspace in the heart of the city 🏡 Hybrid More ❯

scalable systems and high-volume, low latency, transaction/computation applications. Broad understanding of the software development lifecycle, including the application of LLM driven and Data Science DevOps/MLOps/AIOps methodologies. Expertise in data management and analytics, including data structures, data processing, data modelling, and statistical analysis. Knowledge of Python and C# for development and scripting. Leadership: Proven More ❯

GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If you have these skills and would like to find out more, please apply now. More ❯

TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar). Experience working with cloud platforms (AWS, Azure, or GCP). Solid understanding of CNNs, object detection, segmentation, and image classification. Strong More ❯

with distributed systems (Spark, Databricks, etc.). Familiarity with semi-structured and unstructured data formats. Knowledge of machine learning frameworks and how to operationalise models in production. Understanding of MLOps and AI model lifecycle management is a plus. Benefits: 25 Days holiday (excluding bank holidays) – increasing by a day every 2 years. Flexible working options – hybrid. Mental health and wellbeing More ❯

with distributed systems (Spark, Databricks, etc.). Familiarity with semi-structured and unstructured data formats. Knowledge of machine learning frameworks and how to operationalise models in production. Understanding of MLOps and AI model lifecycle management is a plus. Benefits: 25 Days holiday (excluding bank holidays) – increasing by a day every 2 years. Flexible working options – hybrid. Mental health and wellbeing More ❯

in NLP, unstructured data, and information extraction Eagerness to learn, take feedback, and contribute to a collaborative team Nice to Have: Experience with SQL/NoSQL databases Familiarity with MLOps tools (Docker, Git, CI/CD) Exposure to vector databases or semantic search Knowledge of financial datasets or document processing workflows If you’re excited to grow your skills in More ❯

CI/CD pipelines. Experience 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 in time series modelling techniques (e.g. More ❯

a talented team of researchers to improve and refine algorithms for real-world tasks Ensure the scalability and maintainability of production systems, with a strong focus on (low-level) MLOps What You’ll Be Doing (Machine Learning Researcher): Conduct groundbreaking research to develop new algorithms and models for robotics Work on advanced learning approaches such as reinforcement learning and imitation More ❯

deployment of high-impact models (personalisation, churn, demand forecasting, pricing, etc.) into production. Establish governance and standards for model quality, explainability, and bias mitigation across jurisdictions. Drive adoption of MLOps best practices - CI/CD, automated testing, monitoring, feature stores. Partner with Marketing, Digital, Technology, Innovation and local business units to embed intelligence into customer and operational workflows. Champion advanced More ❯

direct experience working with YOLO models being a major plus. Experience with large-scale data processing and database technologies such as MongoDB or other NoSQL databases. Practical knowledge of MLOps principles, including CI/CD pipelines using GitHub Actions . Experience with analytics platforms like Google Analytics and business intelligence tools like Tableau or Power BI. Knowledge of GPU-accelerated More ❯

you will design and develop scalable, cloud-based backend systems using multiple programming languages. You'll contribute to QA, automation, and infrastructure management while supporting DevOps and AI/MLOps practices. Collaboration on architecture, environment lifecycle, and regulatory compliance is key. Be a part of something bigger. At Eddyfi Technologies, we're proud to push the boundaries of innovation to More ❯

their Databricks practice and needs multiple specialists to join this high-impact initiative. 🎯 DATABRICKS TEAM ROLES: Senior Data Engineering Consultant - Databricks/Snowflake focus Senior ML Engineer - Databricks specialisation (MLOps) Senior Platform Engineer - Databricks deployment expert Senior Databricks ML Engineer - Premium specialist role 🏢 Join a Dedicated Databricks Centre of Excellence: You'll be part of a specialist Databricks team delivering More ❯

systems, data pipelines, and ETL processes Familiarity with cloud platforms, particularly Microsoft Azure Understanding of microservices architecture and distributed systems Experience with DevOps practices for AI/ML workflows (MLOps) Strong programming skills in Python and related data science libraries Demonstrated ability to work within solution architecture frameworks Preferred Qualifications Experience with multiple cloud providers beyond Azure Familiarity with container More ❯

deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to validate impact Act as a technical lead within project teams, mentoring mid-level More ❯

you will design and develop scalable, cloud-based backend systems using multiple programming languages. You'll contribute to QA, automation, and infrastructure management while supporting DevOps and AI/MLOps practices. Collaboration on architecture, environment lifecycle, and regulatory compliance is key. As Full Stack Software Engineer, you will have to : Develop scalable software systems for back-end that will be More ❯

AI Engineer include: Strong Data Science Foundations – bring solid grounding in statistics and machine learning, along with strong programming skills – Python preferred. Bonus points if you have exposure to MLOps tools and workflows. Passion for Cutting-Edge AI – You actively experiment with and apply modern AI technologies such as LLMs, RAGs, co-pilots, agentic workflows, and more. You’re always More ❯

model optimization (i.e. quantization, pruning) and model deployment frameworks such as TensorRT, ONNX Runtime, and OpenVINO. Proficiency with CUDA programming and optimizing code for GPU acceleration. Strong background in MLOps practices, including CI/CD using GitHub Actions and containerization with Docker. Excellent problem-solving skills and the ability to thrive in a fast-paced, high-intensity environment. Experience contributing More ❯

and deploying object detection models, particularly within the YOLO family. Familiarity with model optimization techniques such as quantization and pruning, and deployment frameworks like TensorRT and OpenVINO. Experience with MLOps tools and practices, including version control (Git), Docker, and CI/CD with GitHub Actions. Excellent problem-solving skills and the ability to perform in a fast-paced, high-intensity More ❯

leads to ensure consistency and quality Eligible for UK Government Security Clearance (SC minimum, DV preferred) Desirable Experience in client-facing roles or consulting Familiarity with LLMs, AI agents, MLOps or containerised deployments in classified settings Understanding of AI governance, ISO 42001, or model assurance frameworks More ❯

plus Demonstrated experience building APIs to support analytics/research/actuarial functions in an insurance company setting Experience with cloud technologies like Snowflake and Databricks Familiarity with the MLOps framework Exceptional collaboration and relationship building skills More ❯

prompt practices. Proven change leadership: you have driven ≥50% adoption with training and comms. Governance mindset: you have designed guardrails that pass risk and legal review. Working grasp of MLOps/GenAIOps (CI/CD, model registry, data lineage, evaluation). Clear communicator: you can brief boards and coach non-technical teams. Comfortable in a matrix: you align marketing, data More ❯

MLOps Engineer A high-performance company who develop software and hardware products for the entertainment, engineering and life science industries are looking for a MLOps Engineer to join the team in Oxford. The team are looking for an excellent ML Ops Engineer to join their research and development team in Oxford, England. This opportunity is to join the ML Operations … Exposure to cloud based systems e.g. AWS, Azure or GCP (they use AWS) Knowledge of Linux systems including scripting and system configuration. Understanding of how ML tools fit into MLOps pipeline Desirable: Programming experience – ideally C++ or Java Background in DevOps – CI systems, Infrastructure-as-code Location – Oxford (Hybrid working 2 days a week onsite) Salary – Up to More ❯

MLOps Engineer A high-performance company who develop software and hardware products for the entertainment, engineering and life science industries are looking for a MLOps Engineer to join the team in Oxford. The team are looking for an excellent ML Ops Engineer to join their research and development team in Oxford, England. This opportunity is to join the ML Operations … Exposure to cloud based systems e.g. AWS, Azure or GCP (they use AWS) Knowledge of Linux systems including scripting and system configuration. Understanding of how ML tools fit into MLOps pipeline Desirable: Programming experience – ideally C++ or Java Background in DevOps – CI systems, Infrastructure-as-code Location – Oxford (Hybrid working 2 days a week onsite) Salary – Up to More ❯