Summary
Kamyar Salahi is a research engineer with nine years of experience building machine learning systems and infrastructure at the intersection of research and production. He has worked on memory, continual learning, and tool-use for post-training models across top AI labs and academia, including OpenAI, Anthropic, Stanford, and Berkeley AI Research. Kamyar pairs deep research in LLMs, NeRFs, and computer vision with hands-on engineering—shipping low-latency vision models, authenticated container networking for large-scale training, and ML data platforms. Based in San Francisco, he bridges academic rigor (Stanford MS, UC Berkeley BS/MET) with startup and product experience, including a co-founded stealth startup on real-time aerial wildfire tracking. He’s known for squeezing performance out of GPUs (“I make GPUs go brr”) while solving practical problems in memory and continual learning that help models gather the right context for arbitrary workflows.
9 years of coding experience
8 years of employment as a software developer
Bachelor of Science - BS, Business Administration, Bachelor of Science - BS, Business Administration at University of California, Berkeley, Haas School of Business
La Cañada High School
Bachelor of Science - BS, Electrical Engineering and Computer Science, Bachelor of Science - BS, Electrical Engineering and Computer Science at UC Berkeley College of Engineering
Bachelor of Science - BS, Electrical Engineering and Computer Science + Business Administration, Bachelor of Science - BS, Electrical Engineering and Computer Science + Business Administration at UC Berkeley Management, Entrepreneurship, & Technology (M.E.T.) program
Dual Enrollment, Dual Enrollment at University of Illinois Urbana-Champaign
Master's degree, Computer Science, Master's degree, Computer Science at Stanford University
English, Spanish, Persian