enter
ML Platform Engineer
- Eligibility
- Not stated
- Batch
- 2019–2024
- Experience
- Not stated
- Pay
- ₹35–80 LPA
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About this role
About the role: - Build and maintain infrastructure that enables machine learning teams to train, deploy, and monitor models at scale - Develop automation and tooling around ML workflows to reduce friction in the model lifecycle - Design systems for model versioning, artifact management, and reproducible experiments - Work on CI/CD pipelines tailored to machine learning workloads and requirements What you'll work on: - Docker and Kubernetes for containerization and orchestration of ML applications - Cloud platform services to support model training, inference, and data pipelines - MLOps tools and practices that help teams move models from experimentation to production - Monitoring and observability systems that track model performance and system health What we're looking for: - Strong programming ability and solid problem-solving mindset - Hands-on knowledge of machine learning pipelines from training through deployment to monitoring - Practical experience with Docker, Kubernetes, CI/CD workflows, and major cloud platforms - Familiarity with model versioning systems and infrastructure patterns for scaling machine learning workloads