Linden Li is Co-Founder and Chief Architect at Applied Compute, an enterprise AI startup building Specific Intelligence to deploy proprietary in-house agent workforces. Applied Compute raised $100M total from Benchmark, Sequoia, and Lux Capital and works with clients like DoorDash, Cognition, and Mercor.

Linden holds BS and MS degrees in Computer Science from Stanford University and previously served as Member of Technical Staff at OpenAI, where he specialized in scaling AI training infrastructure and contributed to reinforcement learning projects. He also worked at Databricks, MosaicML, NVIDIA, and Stanford AI Lab.

At OpenAI, Linden worked on critical research efforts alongside his co-founders Rhythm Garg and Yash Patil, contributing to the development of reasoning models and coding AI capabilities. He gave talks at NeurIPS on LLM inference fundamentals and trained GPT models from scratch to demonstrate accessible training costs.

Applied Compute emerged from stealth in October 2025 with $80M Series B funding after raising $20M seed round in June 2025 at $100M valuation. The company embeds engineers within client teams to build custom training stacks, agent platforms, and proprietary models in days instead of months.

Applied Compute partners with major enterprises to train RL-powered agents on proprietary data, including DoorDash for merchant onboarding models and Mercor for post-training on expert data from law, investment banking, and consulting. The company's platform enables organizations to build specialized AI agents that continuously learn and improve.