Description

Key Skills: Containerization (Docker, Kubernetes), DevOps, Python, AWS, Kubernetes, GitHub

Roles and Responsibilities:

• Provide L3 support/ development for complex platform incidents escalated
• Troubleshoot issues related to workspace provisioning, model execution, job orchestration, and data connectivity.
• Perform root cause analysis (RCA) and implement permanent fixes for recurring issues.
• Manage platform operations, including upgrades, patching, monitoring, and performance tuning & workspaces. Ensure uptime as a part of the KPI and SLA
• Support data science environments (Python, R, Git) used by analytics and AI/ML teams.
• Enable ML lifecycle activities including experimentation, training, and deployment.
• Implement automation and monitoring improvements to enhance platform reliability.

Skills Required:

• Experience with Domino Data Lab
• Data science platform support and ML workflow orchestration
• Container and orchestration technologies such as Kubernetes, Docker
• Code repository skills like GitHub, GitLab, Bitbucket
• Cloud platforms such as Amazon Web Services
• Amazon SageMaker
• Microsoft Azure Machine Learning

Experience Requirements

• 7-10 years of overall IT experience
• 4+ years supporting data science or analytics platforms
• Experience in life sciences or pharmaceutical environments
• Familiarity with regulated environments (GxP), ITSM tools, and change/release management.

Nice to Have

• Kubernetes administration/ Domino data lab certification
• Cloud certifications (AWS/Azure)
• Exposure to clinical analytics, research data platforms, or AI/ML model development.

Education: Bachelor's Degree in related field

Key Skills

Education

Any Graduate