Javad Azizi is a Senior AI Research Engineer based in California with eight years of experience advancing foundational models, reinforcement learning, and learning-to-rank systems. He holds advanced degrees in ML, operations research and applied mathematics from USC and has combined rigorous theory (bandits, optimization) with production-facing work at Google, DeepMind, Uber, and Amazon. His recent projects span Gemini post-training and on-device GenAI to ranking and best-arm identification algorithms applied in search and recommendation. Javad is skilled at translating statistical rigor and algorithm design into scalable systems, and he has a track record of moving research into product at major platforms. Less obvious: his background in operations research and traveling salesman / simulation optimization informs a practical, optimization-first approach to RL and ranking problems.
8 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD ML and Operations Research, Doctor of Philosophy - PhD ML and Operations Research at University of Southern California
Bachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at Sharif University of Technology
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