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Tier-1 employer, mid-level generalist DevOps/MLOps role with broad skillset increases competition.
MLOps specialization raises industry specificity, but core DevOps and Python skills remain transferable.
No explicit years but multiple mandatory DevOps/MLOps and Python skills imply moderate filter strictness.
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Develop and implement DevOps and MLOps practices including model deployment, monitoring, and versioning.
Manage CI/CD pipelines and automation for machine learning workflows, ensuring code quality, security, and performance.
Collaborate with data science and engineering teams on model lifecycle management and related infrastructure development.
Proficient in Python programming for ML development and production environments.
Experience with DevOps/MLOps including CI/CD pipeline management and automation for ML workflows.
Degree Requirement: B.E/B.Tech.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in managing ML model lifecycle including deployment, monitoring, version control, and reproducibility.
Ability to collaborate cross-functionally with data science and engineering teams on complex ML infrastructure.
Familiarity with frontend development frameworks like Streamlit, TypeScript, Angular, or React is preferred.