7 of 7 Remote MLOps Jobs in the Thames Valley

Engineer Machine Learning Engineer – AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We’re looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that’s reinventing how the world designs More ❯

Engineer - AI for Advanced Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that's reinventing how the world designs More ❯

+ 10–20% bonus (linked to MVP pilot) Location: Slough (Hybrid - 2+ days/week) Stack: Python, LangChain, Semantic Kernel, vector DBs, Azure AI/MLOps Visa: No sponsorship available Interested? Please apply below. More ❯

and vector search architectures Ability to build autonomous agents that interact with APIs, fetch public data and trigger external actions Experience deploying AI solutions on Azure Strong understanding of MLOps, data engineering and model life cycle management Experience embedding AI features into a SaaS or operational technology platform Experience working in the manufacturing industry or with manufacturing, supply chain or More ❯

and vector search architectures Ability to build autonomous agents that interact with APIs, fetch public data and trigger external actions Experience deploying AI solutions on Azure Strong understanding of MLOps, data engineering and model lifecycle management Experience embedding AI features into a SaaS or operational technology platform Experience working in the manufacturing industry or with manufacturing, supply chain or inventory More ❯

Scientists, Data Engineers, and DevSecOps teams , building automation pipelines that accelerate model development and deployment across distributed, cloud-native systems. Key Responsibilities Design, implement, and maintain end-to-end MLOps pipelines for model training, validation, deployment, and monitoring. Develop and automate workflows using Terraform, Kubernetes, Docker , and CI/CD toolchains (GitHub Actions, Jenkins, Argo, etc.). Manage scalable cloud … pipelines. Contribute to the development of a modular, reusable ML platform architecture supporting multi-modal data (genomic, clinical, imaging, etc.). Essential Skills and Experience Proven experience as an MLOps Engineer, Platform Engineer, or DevOps Engineer supporting ML or data science teams. Strong hands-on experience with containerization (Docker) and orchestration (Kubernetes) . Expertise in Terraform , Infrastructure as Code (IaC … Solid understanding of CI/CD pipelines and automated testing frameworks. Experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn. Familiarity with MLflow, Kubeflow, DVC, or similar MLOps tools . Understanding of cloud security principles , IAM, and networking best practices. Proficiency in Python and Bash scripting for automation and tooling development. Version control with Git , and collaborative development More ❯

Lead AI Developer | Hybrid (Slough, 2 days a week) | £75,000–£90,000 + Bonus We’re supporting a founder-led tech business building an AI-first platform within the industrial software sector. This is a hands-on technical leadership More ❯