Tinkerer

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 Tinker

Tinker is our fine-tuning API that empowers researchers and developers to customize frontier AI to their needs — opening access to capabilities that have previously been concentrated in a handful of labs. We manage the infrastructure while allowing Tinkerers full flexibility in training open weights models with their own data, algorithms, and for their own needs. We also share the work we’re doing on post-training science broadly – like On-Policy Distillation – via our Connectionism blog.

About the Role

We're hiring a Tinkerer: a research engineer who builds Tinker by using Tinker, and who helps the open source community build with Thinking Machines' products. You'll work hands-on with real users, write and update cookbook recipes, add library features, and prototype integrations, turning their challenges into product improvements. You’ll also share post-training science and techniques that commonly has not bee known from the labs, like OPD (link to kevins blogpost

This is a technical-first and research heavy role with a major user-facing component, bridging the open source community and our research and infrastructure teams. You'll surface user patterns to guide product and infrastructure priorities, and share what you learn through blog posts, demos, talks, and code examples. It's ideal for someone who is happiest in a code editor or Jupyter notebook, has deep expertise in model post-training, and also enjoys teaching and engaging with a fast-growing developer community.

What You'll Do

• Write, test, and maintain high-quality code examples, recipes, agentic training pipelines, and documentation for Tinker and Inkling, including in our Tinker cookbook.

• Work directly with developers and researchers in the open source community to understand and debug technical issues, gather feedback, and optimize their fine-tuning and deployment pipelines.

• Partner with research and infrastructure teams to turn community patterns and feedback into concrete improvements to Tinker, Inkling, and future models, and develop new post-training recipes.

• Build tools, integrations, and demos that reduce user friction and make it easy to experiment, adopt, and deploy Thinking Machines' models.

• Represent Thinking Machines in the open source community through blog posts, guides, tutorials, livestreams, talks, and conference and meetup appearances.

• Contribute to and help maintain open source libraries, engaging with the community by answering questions, reviewing contributions, and sharing learnings.

• Help shape Tinker's developer experience roadmap, near-term priorities, and long-term product strategy as new models and platform features ship.

Skills & Qualifications

Minimum Qualifications

• 5+ years of experience in developer relations, developer experience, or a software engineering role with significant open source or community-facing work.

• Strong software engineering skills, with experience writing and shipping production-quality Python code.

• Hands-on experience fine-tuning, evaluating, or deploying large language models (LLMs), including supervised and reinforcement learning and how to tune the hyperparameters of these algorithms.

• Comfortable reasoning about model training, fine-tuning, and inference, and able to credibly discuss tradeoffs between different approaches.

Preferred Qualifications

• Deep expertise in post-training LLMs on new domains and improving model capability, including reinforcement learning and agentic training.

• Track record contributing to, maintaining, or growing open source software libraries, and a passion for engaging with open source communities.

• Thoughtful about developer experience, with clear ideas around developer ergonomics, onboarding flow, and sharp edges.

• Experience writing public or internal code examples, tutorials, cookbooks, papers, or technical content that helped others understand and apply technical concepts.

• Comfortable engaging publicly through talks, livestreams, or academic research conferences and meetup appearances.

• Familiarity with multimodal models (text, image, audio) and the tradeoffs involved in training, fine-tuning, and inference.

Logistics

• 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 $300,000 - $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.