2 of 2 Remote Machine Learning Jobs in Oxford

and AI-driven research workflows . You will play a critical role in bridging the gap between data science, bioinformatics, and engineering — ensuring seamless, secure, and reproducible deployment of ML models in production and research environments. You’ll collaborate closely with AI Scientists, Data Engineers, and DevSecOps teams , building automation pipelines that accelerate model development and deployment across distributed, cloud … AI workloads and data processing. Build and maintain feature stores, model registries, and versioning systems to ensure traceability and reproducibility. Implement data ingestion and pre-processing pipelines to support ML and bioinformatics workloads. Collaborate with security and DevSecOps teams to enforce best practices in access control, compliance, and governance . Support AI/ML researchers in model experimentation and infrastructure … optimization. Monitor model and system performance, implement drift detection, and refine automated retraining 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 More ❯

in interpreting analytical results. Build algorithms applicable across varied use cases and markets. Key Skills & Experience Strong experience interfacing directly with customers. Background in data science , including statistical modelling, machine learning, or applied analytics. Proficiency in Python for data analysis, modelling, and cloud application development. Exposure to automotive systems, electrification, or battery applications . Additional knowledge of electrochemistry More ❯