Summary
Noah Jacobson is a Senior Software Engineer and ML specialist with eight years of experience building production ML systems and agentic tooling across Google and Amazon. He designs and ships user-facing agents and AutoML solutions, most recently working on Gemini cloud assistants to create, optimize, debug, and explain Google Cloud infrastructure. At Amazon he led multimodal LLM agent projects for trend detection, recommendations, and in-store stylist chatbots, and earlier owned pricing and taxonomy ML for grocery. His research work at Scale AI focused on data quality for coding and agent evaluation, co-authoring SWEAP-Pro and exploring LLMs as judges for frontier reasoning. Based in California and trained at Stanford in AI, he blends deep learning research with practical SRE-style automation—pursuing a stated mission to automate software engineering before moving on to automating machine learning. An uncommon thread in his career is shipping both low-level infrastructure (datacenter provisioning, temperature optimization) and cutting-edge agentic models, giving him fluency from hardware to high-level ML products.
9 years of coding experience
5 years of employment as a software developer
Master of Science - MS Artificial Intelligence, Master of Science - MS Artificial Intelligence at Stanford University