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 looking for a frontend software engineer to work across product prototyping, internal tools, and frontend infrastructure. As examples of work, you’ll contribute to our frontend monorepo, including the Tinker console and future products applications, and help improve developer experience for fast iteration.
Note: This is an "evergreen role" that we keep open on an on-going basis to express interest. We receive many applications, and there may not always be an immediate role that aligns perfectly with your experience and skills. Still, we encourage you to apply. We continuously review applications and reach out to applicants as new opportunities open. You are welcome to reapply if you get more experience, but please avoid applying more than once every 6 months. You may also find that we put up postings for singular roles for separate, project or team specific needs. In those cases, you're welcome to apply directly in addition to an evergreen role.
What You’ll Do- Prototype and launch new products and user experiences.
- Maintain and iterate on existing UIs, including Tinker.
- Build internal tools (dashboards, consoles) that streamline workflows.
- Evolve frontend infrastructure: design systems, component libraries, build pipelines, testing setups.
- Improve developer experience for local development, deployment, and iteration speed.
Minimum qualifications:
- Bachelor’s degree or equivalent experience in computer science, engineering, or similar.
- Strong experience with modern frontend technologies, tooling, or frameworks (for example, Typescript or React)
- Comfort operating as a frontend engineer and owning projects end-to-end.
- Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
- A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.
Preferred qualifications — we encourage you to apply if you meet some but not all of these:
- Ability to build high‑quality, production-level UIs from prototype to polish.
- Familiarity with React Router, Vite, Turborepo, or similar frameworks.
- Track record contributing to frontend monorepos and shared component libraries.
- Experience with design systems, developer tooling, or internal platforms.
- Familiarity with NodeJS, Python, and/or Rust.
- Experience with AI products or other frontends that scale to large userbases.
- 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 $350,000 - $475,000 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.
Top Skills
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.
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