Soumya Chatterjee is a Machine Learning Engineer at Apple with 12 years of industry and research experience focused on NLP, information retrieval, and ML systems, currently contributing to Siri and Spotlight Search. A Stanford CS master’s graduate and IIT Bombay alumnus, he blends academic rigor—evidenced by TA roles for CS 224N and research on hardware-aware training and distribution-shift retrieval—with production impact from internships at Google and Apple. His research on efficient knowledge updates and policy reuse at Google Research complements hands-on engineering work like enabling zero-shot term translation using LLM prompts and LoRA finetuning to reach >95% term accuracy. An active open-source contributor, he has improved core tooling such as the popular fish shell and implemented RFC-compliant DNS-over-HTTPS changes, showing comfort across systems, backend engineering, and test automation. Based in Seattle, he pairs deep modeling expertise with pragmatic systems engineering to ship robust, research-informed features at scale.
12 years of coding experience
1 year of employment as a software developer
Indian Institute of Technology Bombay
Lilavatibai Podar Sr Secondary School
Pace Junior Science College
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Stanford University
Contributions:3 reviews, 13 commits, 8 PRs in 7 months
Contributions summary:Soumya primarily contributed to the fish-shell project by fixing bugs and enhancing the shell's functionality. Their work included suppressing error messages in the `jobs` builtin, addressing a typo, and adding a new variable `$fish_kill_signal` to track signals that terminated commands. They also implemented the `$fish_job_summary` function, which allows customization of job completion messages. Furthermore, they have modified existing tests and introduced new tests.
Contributions:6 commits, 1 PR, 2 comments in 1 day
Contributions summary:Soumya significantly contributed to the `https_dns_proxy` project by implementing core functionality related to DNS-over-HTTPS communication. They refactored the code to support RFC 8484, switching from a previous JSON format for improved compatibility and code simplification. Key changes included modifications to the HTTPS client, DNS server interactions, and options parsing, improving logging for debugging purposes. Furthermore, the user streamlined the codebase by removing unnecessary JSON-related code.
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Soumya Chatterjee - Machine Learning Engineer at Apple