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Metro location but niche senior ML/LLM and knowledge-graph requirements reduce generalist applicant competition.
Role requires specialized ML, LLM agent, and knowledge-graph expertise, limiting cross-industry transferability.
Explicit 10–16 years, lead experience, and multiple mandatory ML and GCP requirements make filters strict.
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Lead the development and enrichment of the semantic/context layer and AI agents within the knowledge catalog ecosystem.
Use and extend existing Knowledge Catalog APIs to enhance catalog content and improve data quality at scale.
Mentor Senior Data Scientist and collaborate with Data Architects on schema design and query performance for AI-driven catalog enhancements.
10+ years of experience in data science or ML engineering with at least 3 years in a leadership role.
Hands-on experience working with data catalogs/metadata platforms and APIs for data consumption and enrichment.
Strong expertise in building LLM-based agents, LLM evaluation layers, semantic search, NLP/NLU, and knowledge graphs including entity resolution and semantic matching.
Proficient with GCP Vertex AI, BigQuery, ML pipeline orchestration, Python, and graph/query languages; hybrid Bangalore work location.
Experienced leader capable of guiding AI and data-science initiatives focused on knowledge catalog enrichment and quality assurance.
Deep technical skills in large language models, knowledge graphs, and ML pipeline design with operational ownership of production-scale AI agents.
Comfortable working within hybrid environments and mentoring senior data scientists while collaborating cross-functionally with architects to optimize systems.