Verified current Job

Research, Coding Agents

ABOUT THINKING MACHINES

Job Remote Full source details
Thinking Machines Lab San Francisco Source published Sep 20, 2026 Verified 9 hours ago
✓ 100% verification score · Source: Thinking Machines Lab (ashby) · Always confirm final requirements on the original source.
Complete source information imported The available role or programme description, requirements, benefits and source facts were imported from the public official endpoint and formatted for reading.
EmploymentFull-time
Work modeRemote / location-flexible

Overview

ABOUT THINKING MACHINES

Full 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

  • The Coding Agents team makes our models world-class at agentic coding — writing, debugging, and reasoning about code across long-horizon, multi-turn tasks.
  • You'll join a small, high-leverage team responsible for the recipes, data, and infrastructure behind coding capability gains in every model release.
  • The team owns the full coding post-training stack: synthetic and human data generation, RL environments and sandboxes, reward and grading design, and large-scale training runs.
  • This is a research role with real ownership — you'll shape technical direction, not just execute against a spec. Note: This is an "evergreen role" that we keep open on an on-going basis to express interest in this research area. 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
  • Design and run RL training jobs targeting agentic coding capabilities, iterating on recipes and data.
  • Build and improve the sandboxed coding environments and reward signals that models are trained and evaluated against.
  • Generate and curate high-quality synthetic coding data, and build scalable, general-purpose data pipelines.
  • Design evals that measure real-world coding usefulness, and train models against them to deliver concrete improvements in day-to-day usability.
  • Debug and analyze large RL runs to catch confounders, reward hacking, and other RL failure modes.
  • Collaborate closely with infra, evals, and other post-training teams on shared data, joint training runs, and usability improvements — and ship the results into model releases. SKILLS AND QUALIFICATIONS Minimum qualifications:
  • Strong engineering skills, ability to contribute code and debug in complex codebases.
  • Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX). Comfortable with debugging distributed training and writing code that scales.
  • Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding.
  • Clarity in communication, an ability to explain complex technical concepts in writing. Preferred qualifications — we encourage you to apply even if you don’t meet all preferred qualifications, but at least some:
  • Experience building synthetic data pipelines and systems that were adopted by others on your team and remain in use today.
  • Experience owning the end-to-end cycle of identifying gaps in model usability and closing them through custom evaluations and training data.
  • Experience making large-scale agentic RL infrastructure reliable given the long tail of failures that surface at scale.
  • Experience improving the coding capabilities of a frontier model.
  • PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding; or, equivalent industry research experience. 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 $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.

Tips for this job

Practical Job and Scholarship guidance. These tips do not replace official rules or create new eligibility requirements.

  1. Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
  2. Use concrete evidence of relevant work, projects and measurable results rather than generic claims.
  3. Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
  4. Apply through the original employer or official recruitment destination shown on this page.

Verification notes

laptop-ats-crawler v2

Original authoritative source

Job and Scholarship is the discovery and verification layer. Confirm eligibility, dates, salary/funding and application instructions on the original source before submitting anything.

Thinking Machines Lab (ashby) ↗

Browse current Job and Scholarship listings from Thinking Machines Lab (ashby) →

More ways to save

Discover deals, coupons and free courses on our sister site.

Explore DealVorio
Save more with DealVorio: deals, coupons, free courses, apps and books