3 of 3 Contract Azure Machine Learning Jobs in London

for Argos & Nectar Products. Experience Required: MTA (Multi-Touch Attribution) and MMM (Marketing Mix Modelling) Experience Python SQL Pyspark Cloud Technology - Ideally AWS or Azure Machine Learning Experience Accumetric Metrics Experience of working with multi-functional teams Sanderson is committed to barrier-free and inclusive recruitment. We are a Disability Confident recruiter, and More ❯

looking for a Cloud & ML Infrastructure Engineer to join our team. You'll play a key role in designing, building, and maintaining scalable systems that power cutting-edge machine learning workloads. From cloud infrastructure to distributed training environments, you'll help lay the foundation for delivering next-generation AI solutions. Responsibilities Design, deploy, and maintain scalable … high-performance cloud-based infrastructure for ML workloads and APIs. Manage cloud platforms (AWS, Azure, GCP) including ML nodes for local development and distributed training. Install, configure, and monitor servers, ensuring smooth system performance. Optimize shared and local storage for big data ML workloads. Build and scale containerized applications using Docker, Kubernetes, Terraform, etc. Collaborate closely with … experience in a cloud infrastructure or related role (ML experience preferred). Strong scripting skills (Bash, PowerShell, Python, etc.). Hands-on experience with cloud platforms (AWS, GCP, Azure). Proficiency in containerization and orchestration (Docker, Kubernetes). Expertise in managing and optimizing cloud-based systems at scale. Preferred Skills Familiarity with Python (Jupyter) and ML frameworks More ❯

requirements Required Expertise: Extensive ML Ops/ML Engineering experience, particularly in assurance, governance, and monitoring Hands-on knowledge of ML Ops platforms and tools (Kubeflow, MLflow, SageMaker, Azure ML, or equivalent) Proven ability to deploy and maintain AI solutions in regulated or complex operational settings Strong grounding in responsible AI practices, including explainability and fairness Experience More ❯