Hi! My name is Vinjai Vale. I've spent the past few quarters leading the AI Acceleration team at Watershed, where I helped architect the AI-native future of the company, building internal AI agents to accelerate our employees and an agentic platform in our product to serve customers.

I obtained a BS in math and masters in AI at Stanford, graduating in June 2022. My research interests included deep generative models, value-aligned artificial intelligence, and existential risks to humanity. At Stanford, I revived the ACM club and turned it into the largest CS organization on campus, and co-founded the Stanford Existential Risks Initiative.

In my spare time, I enjoy building puzzle boxes, bouldering, experimenting with new recipes, and playing StarCraft II. I am an avid puzzle hunter and helped write the 2023 MIT Mystery Hunt with teammate; I coauthored the Hall of Innovation / Factory Floor metapuzzle, which won Best Metapuzzle at the 3rd Bravo Awards.

Recent work

• Watershed (2022-2025): full-stack product engineering -> AI chief of staff. Built 100+ agents serving all of our employees and contractors, and helped create the infrastructure for AI agents to serve customers in our product. I also built our university recruiting program, designing our hiring profile and interview pipeline and serving as primary hiring manager for the 2025 new grads and interns. Watershed builds the operating system for the climate economy, with ~2% (and growing) of all global GHG emissions under management.
• Scale (2021): ML infra + full-stack software engineering. Conceptualized, researched, and built end-to-end the new active learning feature in the rapidly growing Nucleus product, which helps Nucleus customers curate unlabeled data to prioritize the highest-value data to send to labeling.
• Skiff (2020): full-stack software engineering. Worked on key features like content expiration backend and e2e group workspace UI.
• Jump Trading (2020): quantitative research. Won the interns' algorithmic trading strategies competition and rotated on two trading teams.
• AWS Research (Deep Learning + Digital Signal Processing Group; 2019): ML research. Developed deep latent variable models for end-to-end speech audio enhancement. Published in ICASSP 2021 as co-first author.
• Ng lab (2019): ML research. understanding and predicting treatment response in depression patients. Published in JAMA Network Open.
• Helm.ai (2018): ML research. Developed unsupervised learning algorithms for camera-based depth perception in autonomous vehicles.

Stanford

My most enjoyable month of the year was January, when I competed with my friends in the MIT Battlecode competition. We won first place in 2019, came second place in 2020 and 2022, and made finals in 2021 with team smite. See our 2022 repository, 2019 code and 2019 strategy report.

I also wrote some papers back when I thought I would do an AI PhD.

High school

Graduated from Phillips Exeter Academy in 2018, where I was recognized with the Faculty Prize for Academic Excellence for holding the first rank.

Competed in the 2017 Regeneron Science Talent Search, where I finished in 7th place. Read my paper.

Founded the Phillips Exeter Academy Puzzle Hunt and led the effort to organize three annual 48-hour hunts. See our puzzles and this article. The hunt has become a school tradition and is set to celebrate its tenth anniversary in spring 2026.

In a past life I was an avid math Olympiad contestant. I won first place in the 2015 USA Junior Math Olympiad and went to the Math Olympiad Summer Program. I also wrote a book, 111 Problems in Algebra and Number Theory, for aspiring Olympiad contestants.