69 jobs for “mlops”
PhysicsX New York, United States US$150,000 – US$190,000 pa
Delivery-focused role embedding physics-aware AI models into customer tools, working on-site with clients across aerospace, automotive and energy. Involves building reliable ML data pipelines, manipulating 3D point-cloud and mesh data, and translating R&D outputs into reusable libraries and products. Expects travel of 3-4 weeks per quarter to customer sites worldwide.
Wayve London
Owns the end-to-end release cycle for autonomous-driving AI models, coordinating ML engineering, evaluation, data science, platform, testing and product teams. Defines release gates and promotion criteria from training through validation to fleet deployment, drives regression investigations and rollback decisions, and builds tooling and KPIs to remove bottlenecks in a non-deterministic ML environment.
Department for Transport Birmingham £59,816 – £84,911 pa
Lead the technical delivery of AI solutions across the full product lifecycle, from design and deployment to monitoring and assurance, including classical ML and agentic/LLM-based systems. Work in a government AI and data science team, writing production Python code, running CI/CD pipelines with Terraform on GCP, and building evaluation frameworks to measure model performance.
Aioi Nissay Dowa Europe Oxford £81,322 – £112,488 pa
This role involves leading research in privacy-preserving generative AI, focusing on techniques like differential privacy, federated learning, and secure inference. The scientist will design and validate machine learning models, translate research into deployable systems, and contribute to publications and collaborations within a multi-partner environment. Emphasis is placed on responsible AI, reproducibility, and mentoring junior team members.
Relation Therapeutics London
Lead the platform engineering team owning hybrid on-prem and cloud compute, Kubernetes clusters, MLOps infrastructure and scientific compute environments for machine learning and drug discovery. Set architectural strategy, mature CI/CD and observability, and own platform security and data governance for sensitive patient-derived data, reporting to the VP of Engineering.
Causaly London
Design and ship ML/AI solutions end-to-end, from data exploration to deployment and monitoring, choosing between classical ML, NLP, LLM and agentic approaches. Work closely with product, design and engineering on user-facing AI features, champion model and data quality, and mentor junior engineers in a biomedical knowledge platform team.
Ocado Kraków, Poland
Senior ML engineer role in a cross-craft data science team building prediction, ranking and personalisation systems for an e-commerce platform. Owns the full ML lifecycle on production systems, from experimentation and training through serving, monitoring and MLOps, while coaching others and shaping reusable platform building blocks.
Harnham - Data and Analytics Recruitment London £75,000 – £85,000 pa
Owns the infrastructure, deployment and operational excellence of production machine learning systems within a growing AI and data organisation serving the public sector. Builds ML orchestration pipelines with Dagster, Airflow or Prefect, runs Kubernetes and Terraform/Bicep infrastructure, and maintains CI/CD and observability for models and LLM-powered solutions, working closely with data scientists and client-facing teams.
Entrust London
Lead a team of six applied scientists building vision-language models for document data extraction and sub-5MB models for on-device inference, while staying hands-on about half the time. The role spans roadmap-setting with product and engineering, dataset creation, model training and evaluation, and publishing research on distillation, quantisation and few-shot learning.
