# Product Manager  at Thinking Machines Lab

Thinking Machines Lab is hiring a Product Manager  in San Francisco, United States. It pays $350k-$400k a year and Level rates it Works on AI ●●●○; you can [apply on Thinking Machines Lab](https://jobsbylevel.com/go/dc67f0e8-94dd-42dd-addf-5426be18444a?utm_medium=ai-agent).

AI Level 3, AI centrality 72 out of 100. San Francisco.

## Details

- Company: [Thinking Machines Lab](https://jobsbylevel.com/companies/thinking-machines-lab)
- AI level: AI Level 3 (score 72 out of 100)
- Location: San Francisco
- Salary: $350k-$400k
- Posted: August 4, 2026
- Apply: https://jobsbylevel.com/go/dc67f0e8-94dd-42dd-addf-5426be18444a?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=product-manager-at-thinking-machines-lab-09989e

## 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:

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/product-manager-at-thinking-machines-lab-09989e

Source: https://jobsbylevel.com/jobs/product-manager-at-thinking-machines-lab-09989e

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