Bachelor'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 Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
Strong algorithmic and modeling skills, with solid problem-solving capabilities.
Academic background in NLP, RL, search, or recommendation systems is preferred.
Industry experience with complex document understanding, RAG frameworks, and multi-agent orchestration is a strong plus.
Excellent communication and collaboration skills, with the ability to thrive in cross-functional environments.
Responsibilities
Design and develop sub-agents for search, find, and related tasks over complex enterprise private data with diverse types and heavy schema.
Architect and optimize core algorithms for RAG systems, including retrieval, ranking, and grounding extraction.
Explore novel task decomposition and execution strategies within multi-agent collaboration frameworks.
Analyze offline and online performance signals to identify optimization opportunities and improve user experience and system efficiency.
Collaborate closely with product and platform teams to deliver robust, scalable solutions.