Research Infrastructure Engineer, Research Acceleration

<div class="content-intro"><p data-pm-slice="1 1 []">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.&nbsp;</p> <p>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.</p></div><h2><strong>About the Role</strong></h2> <p>We’re looking for engineers to build the libraries and tools that accelerate research at Thinking Machines. You’ll own internal infrastructure — evaluation libraries, RL training libraries, experiment tracking platforms — and build systems that compound research velocity over time.</p> <p>This is a collaborative role. You will work directly with researchers to identify bottlenecks and pain points. Success means researchers trust your systems to just work and find them a delight to use.</p> <h2><strong>What You'll Do</strong></h2> <ul> <li>Design, build, and operate research infrastructure including evaluation frameworks, RL training systems, experiment tracking platforms, visualization tools, and shared utilities.</li> <li>Develop high-throughput, scalable pipelines for distributed evaluation, reward modeling, and multimodal assessment.</li> <li>Build systems for reproducibility, traceability, and robust quality control across research experiments and model training runs. Implement monitoring and observability.</li> <li>Partner directly with researchers to identify bottlenecks and unlock new capabilities. Own research tooling like a product manager, proactively seeking feedback and tracking adoption.</li> <li>Collaborate with infrastructure, data, and product teams to integrate tools across the technical stack.</li> </ul> <h2><strong>Skills and Qualifications</strong></h2> <p>Minimum qualifications:</p> <ul> <li>Bachelor's degree or equivalent experience in computer science, engineering, machine learning, or similar.</li> <li>Strong software engineering fundamentals with a track record of building reliable, maintainable systems.</li> <li>Proficiency in at least one backend language (we use Python or Rust).</li> <li>Comfort operating across the stack and owning projects end-to-end.</li> <li>Experience in highly collaborative environments involving many different cross-functional partners and subject matter experts.</li> </ul> <p>Preferred qualifications — we encourage you to apply if you meet some but not all of these:</p> <ul> <li>Track record building tooling for researchers that achieved high adoption without top down mandates.</li> <li>Experience building or maintaining ML research infrastructure such as training frameworks, evaluation libraries, or experiment tracking systems.</li> <li>Contributions to open-source ML tools or widely-used internal frameworks at research-focused organizations.</li> <li>Record of publications or technical writing on ML systems, infrastructure, or tooling.</li> <li>Background working closely with ML researchers to understand and solve their tooling needs.&nbsp;</li> <li>Familiarity with distributed systems, modern ML frameworks (PyTorch, JAX), and data processing at scale.</li> <li>Experience with research observability tools, distributed compute frameworks (Ray, Spark), or large-scale evaluation pipelines.</li> </ul> <h2><strong>Logistics</strong></h2> <ul> <li>Location: This role is based in San Francisco, California or New York, NY.</li> <li>Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.</li> <li>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.</li> <li>Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.</li> </ul><div class="content-conclusion"><p><em>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. </em></p> <p><em>Thinking Machines Lab will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the California Fair Chance Act, the San Francisco Fair Chance Ordinance, and any other applicable state or local fair chance ordinance or law.</em></p></div>