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Tier-1 employer, Bangalore metro, and mid-senior ML title create high applicant competition.
Specialized GenAI, ML engineering, and MLOps skills strongly limit cross-industry transferability.
Explicit 7+ years requirement plus mandatory GenAI, MLOps, and cloud production experience raises strictness.
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Own end-to-end development and deployment of production-grade ML and Generative AI systems, including model lifecycle, scalable cloud deployment, and ongoing monitoring.
Partner with senior commercial stakeholders to translate market and customer data into actionable AI-driven insights and analytics solutions that influence decision making.
Lead standardization and automation of ML pipelines, data governance, dashboards, and ensure product engineering quality, data integrity, and compliance with responsible AI practices.
7+ years of hands-on experience in Data Science and ML Engineering with multiple end-to-end production deployments.
Strong Python programming skills, solid computer science fundamentals, and expert SQL proficiency for data validation and access.
Proven expertise in ML model development including traditional ML and deep learning frameworks (PyTorch/TensorFlow), plus Generative AI implementations (RAG, fine-tuning, embeddings, prompt engineering).
Experience with production deployment and operational monitoring on cloud platforms (AWS or Azure); Bachelor’s degree in Engineering, Computer Science, Statistics, Economics, Mathematics, or related quantitative field; Master’s preferred.
Experienced leader with a track record of full ownership from model experimentation through production, including reproducible pipelines and lifecycle management.
Demonstrated ability to develop enterprise-grade Generative AI applications with robust quality controls, security guardrails, and operational readiness.
Skilled in partnering with senior business stakeholders across functions to deliver insight-led storytelling that drives measurable business outcomes in complex, matrixed environments.