MLOps Engineer Location: London, UK (Hybrid – 2 days per week in office) Day Rate: Market rate (Inside IR35 Duration: 6 months Role Overview As an MLOps Engineer, you will support machine learning products from inception, working across the full data ecosystem. This includes developing application-specific data pipelines, building CI/CD pipelines that automate ML model training and deployment, publishing model results for downstream consumption, and building APIs to serve model outputs on-demand. The role requires close collaboration with data scientists and other stakeholders to ensure ML models are production-ready, performant, secure, and compliant.

Key Responsibilities Design, implement, and maintain scalable ML model deployment pipelines (CI/CD for ML) Build infrastructure to monitor model performance, data drift, and other key metrics in production Develop and maintain tools for model versioning, reproducibility, and experiment tracking Optimize model serving infrastructure for latency, scalability, and cost Automate the end-to-end ML workflow, from data ingestion to model training, testing, deployment, and monitoring Collaborate with data scientists to ensure models are production-ready I...