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Remote option plus Bengaluru metro location and established brand drive moderate applicant competition.
Role requires specialized ML/GenAI, MLOps, and enterprise deployment experience, limiting cross-industry transferability.
Explicit 7+ years, 2–4 years ML-specific experience and specific ML/MLOps tech stack make filters strict.
Develop and deploy full-stack AI/ML applications on Cloudera platform targeting real enterprise use cases.
Embed with strategic enterprise customers to prototype, operationalize, and scale AI and agentic systems from prototype to production.
Advise on AI roadmaps and solution design while standardizing successful patterns into repeatable architectures and internal resources.
7+ years of experience building and deploying production-grade systems.
2-4 years of specific experience building ML systems or GenAI and agentic applications.
Hands-on expertise in software engineering, data engineering, and applied AI/ML with modern AI frameworks and tooling.
Work Experience Required: 7+ years in total; 2-4 years in ML/GenAI specifically.
Experienced full-stack ML engineer with a focus on enterprise AI/ML adoption and production deployments.
Proven ability to engage directly with enterprise customer teams in embedded technical roles involving prototyping and scaling AI solutions.
Familiarity or experience with MLOps, LLM orchestration, modern AI stacks, and enterprise data engineering platforms beneficial.