Thinking Machines Lab
Global Public Policy
San Francisco · Senior
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DOL prevailing wage, 2026-27 wage year · Public Relations Specialists (27-3031) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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About the role
- We're looking for a founding policy leader to build and lead Thinking Machines' global public policy function.
- You'll be the company's principal policy strategist and advocate across a wide range of policy issues that shape how Thinking Machines can build and deploy frontier AI responsibly.These could span U.S. federal and state policy, the EU AI Act, international regulatory regimes, export control and national security frameworks. You'll work with leadership to set the company's substantive policy positions, build and lead the team that executes on them, and represent Thinking Machines directly with legislators, regulators, and industry counterparts.
- This is a build role that will take ownership of it end-to-end: hiring and developing a team while scaling the company's engagement across every jurisdiction where policy affects its ability to operate.
Responsibilities
- Set and drive Thinking Machines' global public policy strategy, from U.S. federal legislation and executive action to EU AI Act implementation and policy developments in other key jurisdictions.
- Build and lead the public policy team, including hiring, structuring the function, and establishing how it partners with Research, Product, Safety, Legal, Communications, and the executive team.
- Represent Thinking Machines directly with legislators, regulators, and agency staff, and manage relationships with outside counsel, lobbyists, and advocacy partners.
- Lead the company's engagement on the issues most material to its business: frontier model legislation, safety and disclosure frameworks, open-weight model policy, and societal impact, translating fast-moving developments into clear positions and recommendations for leadership.
- Build and manage coalition relationships with peer labs, industry groups, and trade associations, and represent Thinking Machines in relevant multi-stakeholder forums.
- Develop the internal infrastructure for policy decision-making, including state-of-play tracking, position papers, and clear escalation paths, so policy considerations are built into product and research decisions early.
- Experience building and leading a policy or government affairs function, including hiring and managing a team.
- Strong relationship-building and communication skills, with the ability to represent the company credibly with government officials, industry counterparts, and internal stakeholders alike.
Requirements
- Working knowledge of the US state, federal, and international regulatory landscape for AI, including the EU AI Act, and experience engaging on policy issues across multiple jurisdictions.
- Experience in a frontier AI company, national security, or export control policy context, with familiarity with issues like deemed exports, compute governance, or model release policy.
- Familiarity with the technical fundamentals of frontier AI development (training, fine-tuning, model release processes) sufficient to engage credibly with research and engineering teams.
Nice to have
- we encourage you to apply if you meet some but not all of these:
Compensation
- Depending on background, skills and experience, the expected annual salary range for this position is $300,000-360,000 USD.
Benefits
- Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
Company info
- The mission of Thinking Machines is to build AI that extends human will and judgment.
Visa & Work Authorization
- 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.
This listing is sourced directly from Thinking Machines Lab's careers page and normalized into a canonical job model.