ML Ops Engineer

Prodapt Solutions

7 - 12 years

2 - 6 Lacs

chennai

Posted:1 day ago| Platform:

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Skills Required

ml ops kubernetes snowflake risk management python machine learning docker containerization cloud scripting git data science api design compliance azure ml devops design bash scripting languages ml azure

Work Mode

Hybrid

Job Type

Full Time

Job Description

Role Overview

The ML Ops Engineer designs, implements, and maintains robust machine learning operational pipelines for scalable, reliable, and secure model deployment
This role bridges data science and engineering, ensuring models transition seamlessly from development to production while meeting performance, compliance, and governance standards

Key Responsibilities

ML Pipeline AutomationBuild and maintain CI/CD pipelines for ML models using Git, Azure DevOps, or similar tools
Automate model packaging, artifact storage, versioning, and deployment
Platform Integration Integrate ML platforms (Snowflake, Azure ML, Git-based pipelines) for end-to-end lifecycle support
Collaborate with data engineers to design feature stores and manage training datasets
Governance & Risk Management Enforce model governance policies, including risk management and audit trails
Monitor and optimize ML environments for performance and cost efficiency
API & Infrastructure Enablement Implement secure API endpoints for model consumption
Support containerization and orchestration (Docker, Kubernetes)

Required Skills & Experience

Technical Expertise3+ years in ML Ops or related engineering roles
Proficiency in CI/CD tools, cloud ML platforms, and scripting languages (Python, Bash)
Experience with containerization (Docker), orchestration (Kubernetes), and API design
Collaboration & Communication Strong ability to work across data science, engineering, and IT teams
Tools & Technologies Familiarity with model governance, risk management, and monitoring frameworks

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