About the job
At Thinking Machines Lab, our mission is to empower humanity by advancing collaborative general intelligence. We are dedicated to creating a future where everyone has access to the knowledge and tools necessary to harness AI for their unique needs and aspirations.
Our team consists of scientists, engineers, and builders who have contributed to some of the most popular AI products, including ChatGPT and Character.ai. We have developed influential open-weight models like Mistral and have been active in renowned open-source projects such as PyTorch, OpenAI Gym, Fairseq, and Segment Anything.
About the Role
We are currently seeking a Compensation Partner to join our Operations team. In this pivotal role, you will take ownership of the entire compensation framework at Thinking Machines—from shaping our compensation philosophy and job architecture to collaborating on daily compensation and offer decisions.
Your contributions will directly influence our capacity to attract and retain top-tier talent. We are on the lookout for a Compensation Partner who possesses a strong viewpoint alongside a robust process.
What You’ll Do
- Design and implement a comprehensive compensation framework and programs to attract and retain exceptional talent.
- Advise managers and leadership on compensation decisions regarding offers, promotions, and retention strategies.
- Develop our compensation strategy informed by market research, analytical insights, and your own expertise, acknowledging that traditional benchmarks may lag behind current market realities.
- Collaborate with finance and leadership to establish an equity compensation framework.
- Effectively communicate compensation structures to candidates and employees, fostering trust and transparency.
Skills and Qualifications
Minimum Qualifications:
- 7+ years of compensation experience in a high-growth environment.
- Demonstrated success in building compensation programs from the ground up, preferably in an early-stage setting.
- Experience navigating a competitive and dynamic talent market without relying solely on benchmarks and established processes.
- Ability to articulate a clear and compelling compensation philosophy.
Preferred Qualifications:
- Experience with AI labs, foundation model companies, or high-growth tech firms where compensation practices evolve more rapidly than standard survey cycles.
- Familiarity with the compensation landscape across various functions, including research (PhDs, postdocs, industry researchers), engineering, and non-technical roles, recognizing the differing expectations in each area.

