Summary
Siavash Alemzadeh is a Senior Machine Learning Engineer with nine years of experience building and deploying production ML systems, currently contributing to Uber after a multi-year impact at Microsoft. He specializes in end-to-end ML pipelines, from data onboarding and counterfactual evaluation to latency-optimized LLM-driven recommendation services and RL-based personalizers that served hundreds of campaigns and billions of impressions. His background spans applied research in human-centered reinforcement learning and multiagent control from a PhD in Aeronautics and Astronautics, bringing rigorous modeling and control-theoretic insights to product teams. Siavash also mentors and teaches practitioners as an ML instructor, translating advanced concepts into practical skills for engineers. Colleagues rely on him to bridge research and deployment—improving model throughput, reducing latency, and integrating vision and language features to boost real-world metrics. Based in Sunnyvale, he combines academic depth with a track record of scalable, user-facing AI solutions.
9 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD Aeronautics and Astronautics, Doctor of Philosophy - PhD Aeronautics and Astronautics at University of Washington
Master's degree Statistics, Master's degree Statistics at Penn State World Campus
Bachelor's degree Mechanical Engineering, Bachelor's degree Mechanical Engineering at Sharif University of Technology