Tinkerer

Thinking Machines Lab
San Francisco, CA
On-site

Who this role is best for

Candidates with open-source library development experience and a passion for fine-tuning large language models will find this technical-first role ideal for bridging user needs with product innovation in San Francisco.

Best fit for

  • Engineers who enjoy working with creative users and have a background in open-source software development
    — “ideal for someone who’s who also enjoys talking to creative people”
  • Individuals with hands-on experience in model fine-tuning and a track record of sharing technical insights publicly
    — “Have written public or internal code examples, tutorials, or papers that helped others understand and apply technical concepts”
  • People who thrive in roles that combine infrastructure work with direct user interaction and product shaping
    — “This role is a bridge between Tinker users and our teams”

Things to consider

  • The role involves a significant amount of public communication and sharing of insights through blog posts and demos
    — “Share insights from the field through posts, guides, and talks”
  • The position is based in San Francisco and may require relocation for non-local candidates
    — “relocation support as needed”

How to stand out

  • Highlight your experience with fine-tuning LLMs and your ability to translate technical challenges into product improvements
    — “turning their challenges into product improvements”
  • Showcase contributions to open-source libraries or public documentation that demonstrate your developer experience skills
    — “Experienced with developing software libraries, especially open-source libraries”
  • Emphasize your ability to prototype tools and integrations that simplify complex model customization workflows
    — “Build tools, integrations, and demos that reduce user friction”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • improved user success in building on top of advanced platforms
Typical background
background in machine learning and software development

Skills & requirements

Required

Fine-tuning Large Language ModelsDeveloping Software LibrariesThoughtful About Developer ExperiencePassionate About Engaging With Open-source CommunitiesWritten Public Or Internal Code Examples, Tutorials, Or Papers

Preferred

Experience With Reinforcement LearningExperience With Hyperparameter Tuning

Stack & domain

Fine-tuning Large Language ModelsSupervised And Reinforcement LearningDeveloping Software LibrariesThoughtful About Developer ExperienceEngaging With Open-source CommunitiesReasoning About Model TrainingFine-tuning And InferenceCommunicationProblem-solvingTeamworkAdaptabilityAIMachine LearningSoftware Development

About the role

Original posting from Thinking Machines Lab via Ashby

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 https://thinkingmachines.ai/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 https://thinkingmachines.ai/blog/on-policy-distillation/ – via our Connectionism blog https://thinkingmachines.ai/blog/.

ABOUT THE ROLE

We’re hiring an engineer focused on developer experience to build Tinker while using Tinker — working hands-on with real users and turning their challenges into product improvements. You’ll write and update cookbook recipes, add library features, prototype integrations, and ensure users can customize models smoothly.

This role is a bridge between Tinker users and our teams. You’ll surface user patterns to guide product and infrastructure priorities, and share what you learn through blog posts, demos, and code examples.

This is a technical-first role with a major user-facing component. It’s ideal for someone who’s who also enjoys talking to creative people. Tinker is flexible by design to empower novel and ambitious use cases for model fine-tuning — your job is to help them succeed.

WHAT YOU'LL DO

  • Write, test, and maintain high-quality code examples, recipes, and documentation in the Tinker cookbook https://github.com/thinking-machines-lab/tinker-cookbook/tree/main/tinker_cookbook.
  • Work directly with a variety of users to debug technical issues and optimize their fine-tuning pipelines.
  • Partner with internal research and infra teams to identify and prioritize improvements to Tinker’s developer experience.
  • Build tools, integrations, and demos that reduce user friction and make it easy to experiment and deploy models.
  • Share insights from the field through posts, guides, and talks.
  • Help develop Tinker’s near-term roadmap and long-term product strategy.

SKILLS & QUALIFICATIONS

Enabling user success in building on top of an advanced platform is a skill that can be developed through many paths. You might demonstrate that you have it if you:

  • Experienced with fine-tuning large language models (LLMs) with supervised and reinforcement learning, and how to tune the hyperparameters of these algorithms.
  • Experienced with developing software libraries, especially open-source libraries.
  • Are thoughtful about developer experience, with clear ideas around developer ergonomics, onboarding flow, and sharp edges.
  • Are passionate about engaging with open-source communities, whether by contributing code, answering questions, or sharing learnings.
  • Have written public or internal code examples, tutorials, or papers that helped others understand and apply technical concepts.
  • Are comfortable reasoning about model training, fine-tuning, and inference, and can credibly discuss tradeoffs between different approaches.

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 - $350,000 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.

Source: Thinking Machines Lab careers (Ashby)

Similar roles