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Known enterprise brand, remote tag, and Bangalore metro increase applicant competition.
High—role needs applied ML, enterprise deployment, and MLOps experience tied to domain.
Explicit 7+ years, ML-specific 2–4 years, and specialized AI/MLOps tech requirements.
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Develop and deploy full-stack AI/ML applications on Cloudera platform demonstrating enterprise use cases.
Collaborate directly with customer teams to move AI/agentic use cases from prototype to production readiness.
Standardize successful AI solutions into repeatable architectures, productized solutions, and internal resources while advising customer AI strategies.
7+ years building and deploying production-grade systems.
2-4 years experience in ML systems or Generative AI and agentic applications.
Strong skills in software engineering, data engineering, and applied AI/ML with modern AI frameworks.
Work Experience Required: 7+ years overall; 2-4 years in ML/GenAI domain.
Experienced full-stack ML engineer capable of embedding with enterprise customers to design and deliver scalable AI solutions.
Skilled in bridging customer engineering, AI innovation, and enterprise deployment with consulting or solution architecture exposure.
Proficient with modern AI/ML tools and frameworks and familiar with distributed data engineering platforms (e.g., Apache Spark, Kubernetes).