Product Manager

Thinking Machines Lab Inc.; San Francisco (CA); On-site; USD 350,000 - 400,000; Full time

Benefits offered by this job

Health, dental and vision benefits

Unlimited PTO

Paid parental leave

Relocation support

Job summary

Thinking Machines Lab Inc. is seeking multiple product leaders to turn research, models, and infrastructure into understandable, usable products.

You will shape direction, engage developers and researchers, and drive decisions from discovery through sustained adoption in a fast-paced setting. The role emphasizes technical depth in AI/ML, product judgment, and strong collaboration with research, engineering, design, and GTM teams to deliver reliable, scalable solutions.

Qualifications

• Experience leading a technically complex product with measurable outcomes.
• Technical depth in AI/ML, training or inference, or production infrastructure.
• Ability to reason with engineers and researchers about constraints and tradeoffs.
• Strong product judgment and prioritization.
• Experience using customer insight and data to guide development.
• Ability to drive ambiguous work across teams.

Responsibilities

• Set product direction, priorities, and success measures for your area, connecting user needs with research progress, engineering capabilities, and business opportunity.
• Build direct relationships with developers, researchers, and enterprise users. Understand their workflows, test assumptions, and distinguish individual requests from problems worth solving broadly.
• Turn ambiguous opportunities into concrete decisions: who we’re building for, what problem matters most, what to ship first, and what evidence would change our approach.
• Partner at technical depth with research and engineering. Depending on your focus, this could mean shaping model evaluations and release priorities, improving training APIs and workflows, or defining serving performance and reliability requirements.
• Define quality through real use: whether users can accomplish their tasks, improve their models, understand failures, and make informed tradeoffs between capability, speed, and cost.
• Make advanced capabilities accessible through thoughtful APIs, interfaces, documentation, examples, and product defaults, while preserving the flexibility expert users need.
• Lead work from discovery through launch and iteration, resolving dependencies and making clear decisions about scope, readiness, and tradeoffs. Partner with safety and security teams where those decisions affect access and trust.
• Connect product decisions to adoption and sustainable economics, including pricing, packaging, and the cost of delivering a dependable experience.
• Do the hands‑on work needed to move the product forward—trying a training recipe, inspecting model outputs, investigating a failed workflow, analyzing latency data, or working through a customer’s integration.

Skills

Technical depth

Product leadership

Cross-functional collaboration

Decision making under uncertainty

Customer insight

Stakeholder management

Job description

About Thinking Machines

The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it.

About the Role

Thinking Machines builds AI that extends human will and judgment. We’re hiring multiple product leaders to help turn our models, research, and infrastructure into products that people can understand, shape, and use to do meaningful work.

Your focus could include our platform for customizing models; our model family; or the path from experimentation to reliable production deployment. We are looking for product leaders who will stretch their strengths across the most important problems ahead. Across these areas, the work starts with understanding what users are trying to accomplish, identifying where our technology can make a meaningful difference, and deciding what to build next.

Many of the questions are still open. How do we help people turn their expertise into better models? Which model capabilities unlock valuable new applications, and how do we know they work in practice? What does it take to make training and inference fast, reliable, and economical? How do we give users meaningful control while making powerful technology easier to use?

You’ll work closely with research, engineering, design, and GTM to answer these questions and ship. The strongest candidates combine technical depth with product judgment, learn through direct contact with users, and take responsibility for outcomes from early exploration through sustained adoption.

What You’ll Do

• Set product direction, priorities, and success measures for your area, connecting user needs with research progress, engineering capabilities, and business opportunity.

• Build direct relationships with developers, researchers, and enterprise users. Understand their workflows, test assumptions, and distinguish individual requests from problems worth solving broadly.

• Turn ambiguous opportunities into concrete decisions: who we’re building for, what problem matters most, what to ship first, and what evidence would change our approach.

• Partner at technical depth with research and engineering. Depending on your focus, this could mean shaping model evaluations and release priorities, improving training APIs and workflows, or defining serving performance and reliability requirements.

• Define quality through real use: whether users can accomplish their tasks, improve their models, understand failures, and make informed tradeoffs between capability, speed, and cost.

• Make advanced capabilities accessible through thoughtful APIs, interfaces, documentation, examples, and product defaults, while preserving the flexibility expert users need.

• Lead work from discovery through launch and iteration, resolving dependencies and making clear decisions about scope, readiness, and tradeoffs. Partner with safety and security teams where those decisions affect access and trust.

• Connect product decisions to adoption and sustainable economics, including pricing, packaging, and the cost of delivering a dependable experience.

• Do the hands‑on work needed to move the product forward—trying a training recipe, inspecting model outputs, investigating a failed workflow, analyzing latency data, or working through a customer’s integration.

Skills and Qualifications

• Experience leading a technically complex product, with clear examples of what you shipped, the decisions you made, and the outcomes you improved.

• Technical depth in at least one relevant area, such as AI models and applications, ML training or inference, developer platforms, or production infrastructure.

• Ability to reason with engineers and researchers about technical constraints and tradeoffs, and translate that understanding into sound product decisions.

• Strong product judgment: identifying important problems, choosing among plausible approaches, and setting priorities with incomplete information.

• Experience using customer insight, quantitative evidence, and hands‑on investigation to guide development and evaluate results.

• Ability to drive ambiguous work across teams, communicate clearly, and follow through after launch.

Preferred Qualifications

• Background as an engineer or technical founder before moving into product leadership.

• Experience operating in a startup, lab, or new product area where the product direction and roadmap weren’t handed to you.

• Comfortable moving between a strategic narrative and a specific technical detail without losing judgment.

• Experience taking a technical product from early usage through to reliable, scaled adoption.

• Experience building trust with technical users through evidence, responsiveness, and follow‑through.

• Willingness to get hands‑on, learn unfamiliar domains, and do the work needed to make a product succeed.

We’re looking for complementary strengths across multiple hires. You do not need experience in every area above; you should bring depth in some and the curiosity and judgment to learn others.

Logistics

• Location: This role is based in San Francisco, CA.

• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $400,000 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.