Building Intelligence, the Right Way

Haize

/hāz/ | verb

To rigorously test an LLM or agent with the purpose of preemptively discovering all of its failure modes

Doing Our Life’s Work

We’re not here to write GPT wrappers or get rich quick off the AI bubble. We're here to work on the hardest, most fundamental technical problem in AI: making it safe, reliable, trustworthy, and ready for the real world. We are assembling a team of world-class talent in service of this mission.

Our early team consists of an MIT PhD with 21,000+ citations in Physics and ML, a Datadog Engineering Manager who led their AI observability team, a Citadel quant with a huge open-source presence, ex-founders from Y Combinator, Stanford PhD dropouts, and more.

We’re looking for brilliant, high-agency, low-ego rockstars to join us on this crusade. We want the best of the best and firmly believe greatness begets greatness.

Come here to push yourself hard, learn things fast, experience unmatched excellence, and do your life's work.

Technology

Haize Labs is in the business of developing frontier research and technology. To build AI systems you can trust, we intensely focus on the following:

  • Synthetic data generation and prompt optimization, applied to dynamic testing and red-teaming.
  • Automatic evaluator, judge, and reward models that are hyper-specific to customer use cases.
  • Robustness guarantees for AI behavior.
  • Denoising and rapidly distilling human preferences into AI systems.
  • Efficiently & continuously improving AI systems.
Check out our technology

Team

Leonard Tang

Co-Founder, CEO

Steve Li

Co-Founder

Constantin Weisser

Member of Technical Staff

Nimit Kalra

Member of Technical Staff

Jack Friedson

Member of Technical Staff

Yarin Gal

Advisor

Caleb Sima

Advisor

Rumman Chowdhury

Advisor

Sanji Alwis

Advisor

Careers

Member of Technical Staff (Engineering)

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Member of Technical Staff (Research)

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Research Intern

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CUSTOMERS & INVESTORS

Trusted by the Best. Backed by the Best.

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Haize Labs brings your AI application out of POCs and into production.

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