Summary
Mohit Raghavendra is a Machine Learning Research Engineer with seven years of cross-domain experience building and deploying ML systems, currently advancing post-training RL research for coding and tool-use agents at Scale AI. He holds an MS in Computer Science from Georgia Tech and has led productization efforts as the third engineer at Tensorlake, shipping a Document AI line from design to launch. Earlier roles include quantitative and software engineering at Goldman Sachs, where he built models and systems for market analytics, and research work focused on compute- and data-efficient fine-tuning of LLMs for complex reasoning. Mohit combines academic rigor with production engineering chops, moving models from experimental setups into scalable pipelines. Based in San Francisco, he blends deep learning research, RL training workflows, and practical ML engineering—often optimizing for cost and evaluation efficiency in real-world deployments. Colleagues describe him as someone who comfortably navigates both low-level systems trade-offs and high-level model evaluation strategies.
7 years of coding experience
3 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Georgia Institute of Technology
Bachelor of Technology, Information Technology, Bachelor of Technology, Information Technology at National Institute of Technology Karnataka
English, Hindi, Kannada