ML Ops Engineer

Prodapt

3 years

0 Lacs

chennai tamil nadu india

Posted:1 day ago| Platform:

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Skills Required

ml learning model deployment data engineering development compliance governance pipeline git azure devops automate packaging storage versioning design training risk management audit api support containerization orchestration docker scripting python kubernetes collaboration monitoring

Work Mode

On-site

Job Type

Full Time

Job Description

Overview

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.

Responsibilities

Key Responsibilities

ML Pipeline Automation
Build 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).

Requirements

Required Skills & Experience

Technical Expertise
3+ 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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