Aahil Mehta is a Senior Software Engineer in the Bay Area with nine years of experience building large-scale recommender and retrieval systems, currently researching foundational user modeling architectures at Google to improve ranking and predictive models. He has led JAX-based training infrastructure and driven multiple cross-team landings that delivered significant incremental ARR, and contributes to Keras/JAX integrations—optimizing kernels, data transfer, and TensorBoard reporting. Comfortable bridging research and production, he combines deep ML engineering with hands-on systems optimization and a background tutoring functional and JVM languages. Outside core product work, he consults in venture as a fellow, signaling a knack for spotting technical opportunities and translating them into impact.
9 years of coding experience
4 years of employment as a software developer
Master of Engineering - MEng Computer Science, Master of Engineering - MEng Computer Science at Imperial College London
High School, High School at Blundell's School
Secondary school, Secondary school at The Cathedral and John Connon School
Contributions:3 reviews, 6 PRs, 4 comments in 6 months
Contributions summary:Aahil made several contributions focused on optimizing and extending the Keras backend for the JAX framework. These include speeding up `in_top_k` implementation, accelerating host-to-device data transfer, and adding support for JAX named scopes. They also addressed a bug related to rank computation and made improvements to the `TensorBoard` callback for reporting steps per second. Furthermore, the user allowed passing custom dataset adapters and fixed embedding issues.
Contributions:9 pushes, 1 branch in 5 years 1 month
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