Principal Applied Scientist - CoreAI

Developing LLM prompts, agents and query execution workflows, often with tight latency constraints Lead state of the art research incorporation into techniques shipped to production. Proactively develop and build metrics to use across the full range of search engine components. Seek out and incorporate customer feedback into dataset construction, evaluation, and technique development. Lead technical excellence and contribute to experimentation infrastructure and proofs-of-concept using AI coding agents. Advances the quality of the team's experimental codebase to ensure experiments are efficient and repeatable. Nurtures collaborative relationships with product management, engineers, and other functions across products. 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. Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 3+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping. Experience with agentic coding systems, including scaffolding for long-running agents. Experience with hybrid collaboration skills, with clear async/sync communication and teamwork. Experience defining task-specific metrics and evaluation datasets.