Machine Learning Engineer

Working alongside Data Scientists, Data Engineers and IT teams, you will play a key role in taking machine learning models from concept through to production, ensuring they are scalable, automated and fully monitored throughout their lifecycle., * Design, build and deploy production-ready machine learning pipelines.

• Work closely with Data Scientists to develop scalable ML solutions that meet business and technical requirements.
• Build and maintain CI/CD pipelines for machine learning deployments.
• Develop and manage containerised ML applications using modern virtualisation technologies.
• Implement robust model monitoring, retraining and performance optimisation processes.
• Design and maintain data pipelines to support AI services and model deployment.
• Ensure high standards of code quality, version control and dependency management.
• Support production environments by troubleshooting, monitoring and improving deployed ML services.
• Collaborate with cross-functional teams including Data Science, Engineering, Infrastructure and Operations.
• Drive best practices across MLOps, automation and industrialised machine learning delivery.

• Minimum 4 years’ commercial experience as a Machine Learning Engineer or MLOps Engineer.
• Advanced Python development skills.
• Strong experience with containerisation technologies (Docker/Kubernetes or similar).
• Experience building and maintaining CI/CD pipelines (GitLab CI or equivalent).
• Experience with model, code and data versioning.
• Strong knowledge of package and dependency management.
• Experience working with PostgreSQL.
• Strong understanding of Agile delivery methodologies.

Desirable Experience

• Apache Spark or other big data technologies.
• ETL/ELT pipeline development.
• Data flow processing.
• Integration across distributed systems and enterprise platforms.
• Model optimisation and compression techniques.
• Data visualisation tools.
• Experience deploying AI solutions into enterprise production environments.