Thinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence. We're building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals.
We are scientists, engineers, and builders who’ve created some of the most widely used AI products, including ChatGPT and Character.ai, open-weights models like Mistral, as well as popular open source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything.
We're hiring a compensation partner to join our Operations team. You'll own the full spectrum of compensation at Thinking Machines – from building our philosophy and job architecture to partnering on day-to-day offer and pay decisions.
This role directly impacts our ability to hire and retain exceptional talent. We're looking for a compensation partner who brings a point of view, not just a process.
What You’ll Do- Design and implement Thinking Machines’ overall compensation framework and programs to attract and retain highly sought-after talent.
- Advise managers and leadership on pay decisions across offers, promotions, and retention.
- Establish our compensation strategy based on market research, analysis, and your own judgment, with awareness that standards benchmarks lag the reality of the talent market.
- Build the equity compensation framework in partnership with finance and leadership.
- Communicate compensation to candidates and employees in a clear way that builds trust.
Minimum qualifications:
- 7+ years of compensation experience in a high-growth environment.
- Track record building compensation programs from the ground up, ideally in an early-stage environment.
- Experience operating in a competitive and dynamic talent market without relying on benchmarks and mature processes.
- Ability to articulate a clear point of view on good compensation philosophy.
Preferred Qualifications
- Experience at an AI lab, foundation model company, or high-growth tech company where compensation moves faster than survey cycles.
- Familiarity with the compensation landscape across research (PhDs, postdocs, industry researchers), engineering, and non-technical functions, and how expectations differ meaningfully across all three.
- Location: This role is based in San Francisco, California
- Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $250,000 - $425,000 USD.
- Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
- Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
As set forth in Thinking Machines' Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
Thinking Machines Lab will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the California Fair Chance Act, the San Francisco Fair Chance Ordinance, and any other applicable state or local fair chance ordinance or law.
Skills Required
- 7+ years of compensation experience in a high-growth environment
- Experience building compensation programs from the ground up
- Ability to articulate a clear point of view on good compensation philosophy
What We Do
Thinking Machines Lab is an artificial intelligence research and product company. We're building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals. While AI capabilities have advanced dramatically, key gaps remain. The scientific community's understanding of frontier AI systems lags behind rapidly advancing capabilities. Knowledge of how these systems are trained is concentrated within the top research labs, limiting both the public discourse on AI and people's abilities to use AI effectively. And, despite their potential, these systems remain difficult for people to customize to their specific needs and values. To bridge the gaps, we're building Thinking Machines Lab to make AI systems more widely understood, customizable and generally capable. We are scientists, engineers, and builders who've created some of the most widely used AI products, including ChatGPT and Character.ai, open-weights models like Mistral, as well as popular open source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything.
