onsite
MLOps Engineer 12 months - Coventry Building Society
MLOps Engineer
MLOps Engineer tasked with designing, developing, and testing end‑to‑end machine learning pipelines using Python, Docker, Kubernetes, and AWS, while implementing CI/CD workflows and MLflow for model tracking and deployment.
About the role
Key Responsibilities
- Design, develop, and test scalable machine learning and data engineering solutions in Python.
- Containerise models and services with Docker, orchestrate with Kubernetes, and deploy to AWS environments.
- Implement CI/CD pipelines for automated testing, model validation, and continuous delivery.
- Integrate MLflow for experiment tracking, model registry, and lifecycle management.
- Collaborate with data scientists and product teams to translate business requirements into robust ML solutions.
Requirements
- Strong experience in Python and data engineering best practices.
- Hands‑on expertise with Docker, Kubernetes, and AWS services (EKS, S3, SageMaker).
- Proficiency in CI/CD tools (GitHub Actions, Jenkins, ArgoCD) and MLflow.
- Solid understanding of version control, testing, and monitoring of ML models.
- Excellent problem‑solving skills and ability to work in an agile environment.
Skills
pythondockerkubernetescicdawsmlflow