Summary
Sneha Mehta is a research scientist and NLP-focused AI/ML engineer with 13 years of experience building production-grade conversational AI and billion-scale recommender systems. Based in the San Francisco Bay Area, she has driven applied research and engineering across Meta, TikTok search and recommendations, Twitter Cortex research, and BloombergGPT post-training efforts. Her background spans both deep research—PhD-level training and work on knowledge graphs and recommender architectures—and hands-on productionization of large models and search relevance. She has practical experience in localization and machine translation from internships at Netflix and early R&D at DreamWorks, reflecting a breadth from creative pipelines to large-scale ML systems. Known for bridging research and product, she often moves prototypes into live serving environments at scale. A detail that sets her apart is combining formal math training in algebra and number theory with deep-learning specialization, informing rigorous model design and evaluation.
13 years of coding experience
7 years of employment as a software developer
Deep Learning Reinforcement Learning Summer School, Deep Learning Reinforcement Learning Summer School at University of Alberta
BITS Pilani, Birla Institute of Technology and Science
Doctor of Philosophy (Ph.D.), Doctor of Philosophy (Ph.D.) at Virginia Tech
Algebra and Number Theory, Algebra and Number Theory at Harish-Chandra Research Institute
English