Principal Applied Scientist India Karnataka Bangalore

Job description

Advance retrieval quality science through SEVALs, evaluation frameworks, and metrics for Recall@K, grounding quality, citation correctness, freshness, coverage, and task success. Develop techniques for multi-hop retrieval, cross-source reasoning, semantic enrichment, knowledge graphs, and agent memory. Build trust-aware AI systems that respect enterprise permissions, provenance, and authorization. Pioneer autonomous knowledge acquisition, including relationship discovery, metadata inference, summarization, and knowledge graph generation. Partner with engineering and product teams to bring scientific innovations into production at hyperscale. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research). OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research). OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research). OR equivalent experience. Proven track record of translating research into large-scale production systems. These requirements include but are not limited to the following specialized security screenings: Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) - OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) - OR equivalent experience. 8+ years of experience across ML with a proven record for applying ML across production systems. Experience with enterprise AI, retrieval systems, agent architectures, or knowledge platforms, evals. Experience building evaluation frameworks and quality metrics for Agentic systems. Experience in enterprise space. Proven ability to influence platform architecture and align cross-team roadmaps.