ML OPS Engineer

LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.

A little about us...

Role: ML-OPS Engineer

Location: Remote

Job Description:

Design implement and manage end-to-end automation of the machine learning lifecycle including model training validation deployment and retraining pipelines

Develop and maintain CICD pipelines to enable seamless integration testing and deployment of machine learning models into production environments

Deploy monitor and manage ML models in production ensuring high availability scalability and performance of inference services

Implement model monitoring logging and ing frameworks to track model performance detect datamodel drift and trigger automated retraining processes

Collaborate with data engineers data scientists and platform teams to streamline data pipelines and ensure reliable data flow for ML workflows

Ensure governance versioning and traceability of ML artifacts adhering to enterprise security compliance and audit requirements

Skills

Mandatory Skills : Azure Machine Learning, Industrial AI - Machine Learning (ML), Machine Learning - AIOPS, Python, ThoughtMachine

Good to Have Skills : AI/ML Testing, CI/CD Architecture, MLOPS, Model Life Cycle Management

LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.