Company: Global Technology organization
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
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