MLOps Engineer

Responsibilities

• As the Machine Learning Ops Engineer for the AI Team you will:
• Work closely with the Data Science team and the Data Engineers and DevOps teams in order to deploy machine learning models. Specifically execute continuous integration and continuous delivery (CI/CD) activities to release ML code and ML pipelines into a Production environment
• Maintain the Machine Learning pipeline and make sure everything is running accurately and reliably
• Liaise with senior stakeholders across the Data function and the wider business
• Use industry best practices such as code reviews, pull requests, and peer testing to ensure high quality AI/ML deliverables
• Build AI/ML model performance benchmarking, evaluation, monitoring capabilities and facilitates resolution of issues with the appropriate teams

Must Have

• Proven industry/commercial/research lab experience (2+ years) deploying machine learning models and maintaining ML pipelines, orchestration, deployment, monitoring, & support
• Experience creating and maintaining deployment pipelines with CI/CD tools (2+ years)
• Knowledge of cloud technologies (e.g. AWS) and Extensive Programming experience in Python & SQL
• Experience in containerization and orchestration (such as Docker, Kubernetes)
• Practical Knowledge of Machine Learning models in commercial settings
• Good communication skills

Nice to Have