Description

You will own the implementation and maturity of Machine Learning Operations across data science projects.

This role is on-site.

Responsibilities

• Research and implement MLOps tools, frameworks, and platforms for Data Science projects.
• Manage deployment, inference, monitoring, and retraining pipelines.
• Raise MLOps maturity within the organization by managing a backlog of activities.
• Introduce modern, agile, and automated approaches to Data Science methodology.
• Conduct internal training on MLOps tools and usage.

Required Skills

• 5+ years of total experience, with 2+ years specifically in MLOps.
• Strong experience with Kubernetes and Docker.
• Expertise in Python and Data Science workflows.
• Hands-on experience with CI/CD practices.
• Working knowledge of AWS.
• Familiarity with Machine Learning model deployment.
• Experience with Kubeflow.

Preferred Skills

• Knowledge of Bash and Unix command line toolkit.
• Understanding of model monitoring, drift detection, and experiment tracking.

Key Skills

Education

Any Graduate