Rahul Khanna
Staff Machine Learning Engineer at Jimini Health
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolRahul Khanna is a Staff Machine Learning Engineer in New York with 11 years of experience building applied ML products and research-driven NLP systems. He combines academic rigor from USC—where he contributed to multiple ACL/EMNLP papers on information extraction, numerical commonsense, and forecasting—with hands-on production experience at startups and companies like EvenUp, Vimeo, impact.com, and Jimini Health. As a founding ML engineer and later engineering manager, he has led teams shipping scalable data pipelines, fraud detection and recommendation prototypes, and now develops long-term LLM therapy companions for digital health. Rahul is comfortable across the stack—from Spark and cloud data engineering to model research and HCI-informed productization—and has a track record of turning research ideas into deployable systems. Colleagues value his blend of deep NLP expertise and pragmatic engineering, plus a habit of surfacing annotation and evaluation efficiencies that accelerate model iteration.
11 years of coding experience
9 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at University of Southern CaliforniaBachelor of Science (BS) Computer Science, Bachelor of Science (BS) Computer Science at Columbia Engineering
English, French, Hindi, Chinese
Github Skills (34)
fact6
sequence5
nlp5
topic-modeling5
deep-learning5
lda5
machine-learning5
sequence-labeling5
probing5
pytorch5
face4
crowdsourcing4
tagging4
acl4
crowd4
Programming languages (4)
Github contributions (5)
Rahul-Khanna/danny
Oct 2018 - Sep 2019
Contributions:26 commits, 25 pushes in 10 months
Rahul-Khanna/NExT
Nov 2020 - Jul 2021
Replication of Source Code for paper "Learning from Explanations with Neural Execution Tree", ICLR 2020 using Pytorch and spaCy
Contributions:12 PRs, 601 pushes, 3 branches in 7 months
pytorchnlpiclrexplanationsdeep-learning
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