Goodfire is a San-Francisco-based AI research lab that leverages interpretability techniques to design safer, more controllable models and unlock scientific discoveries.
<div class="content-intro"><h2><strong>About Goodfire</strong></h2> <p>Goodfire is a research company using interpretability to understand, learn from, and design AI systems. Our mission is to build the next generation of safe and powerful AI—not by scaling alone, but by understanding the intelligence we're building.<br><br>Scaling has proven powerful, but today's approach is fundamentally limited: we can't meaningfully understand, debug, or shape what models learn. Every engineering discipline has been gated by fundamental science and AI is at that inflection point now.</p> <p>We're advancing the science of how AI systems actually work. Treating models as black boxes is an unnecessary handicap—we have access to the structures inside them, and understanding those structures lets us steer what models learn, make them safer and more useful, and extract the vast knowledge they contain. Our goal is to make AI that can be understood, debugged, and shaped like software.</p> <p>Goodfire is a public benefit corporation headquartered in San Francisco with a team of the world’s top interpretability researchers and engineers from organizations like OpenAI and DeepMind. We're backed by over $200M from B Capital, Menlo Ventures, Lightspeed, Eric Schmidt, and others.</p></div><h2><strong>About the Role</strong></h2> <p>We're looking for a highly technical Head of Engineering to grow our core platform. At Goodfire, we believe that leaders need to be in the trenches with their team and that engineering leaders also need to be exceptional engineers. We're looking for someone who can do everything it takes to ensure our core platform’s success from developing clean software interfaces for public consumption, making large training runs go smoothly, and ensuring success with our customers and design partners. You’ll have extremely high ownership over a critical core of the business.</p> <p>You'll also be responsible for recruiting outstanding machine learning engineers from top AI labs to work on our mission. The right candidate is someone with existing networks in the frontier AI community and a proven track record of attracting and retaining top technical talent in a competitive market.</p> <h2><strong>Key Responsibilities</strong></h2> <p><strong>Be a Key Technical Contributor</strong></p> <ul> <li>Direct technical execution at the highest level is expected for all leaders.</li> <li>Convert state-of-the-art research into scalable, product-grade tools with urgency.</li> <li>Oversee infrastructure for model interpretability, training, and inference at frontier scale.</li> </ul> <p><strong>Build an Exemplary Engineering Team</strong></p> <ul> <li>Recruit, hire, and retain top machine learning engineers from leading AI research labs.</li> <li>Develop and execute a hiring strategy that positions Goodfire as a destination for the best engineers in the field.</li> <li>Foster a high-performance culture equipped to tackle some of the hardest problems in AI.</li> </ul> <p><strong>Own Outcomes End-to-End</strong></p> <ul> <li>Drive adoption of Goodfire's core platform.</li> <li>Collaborate directly with customers and go-to-market teams.</li> <li>Shape and reinforce Goodfire's culture and values as the company scales.</li> </ul> <h2><strong>What You'll Bring</strong></h2> <p><strong>Required Experience</strong></p> <ul> <li>10+ years of engineering experience, with 5+ years in engineering leadership roles.</li> <li>Demonstrated success building and scaling engineering teams at high-growth startups or frontier AI labs.</li> <li>Exceptional track record recruiting machine learning engineers from top AI organizations.</li> <li>Deep technical expertise in ML infrastructure, distributed systems, and large-scale model training.</li> <li>Hands-on proficiency with PyTorch or JAX, modern ML tooling and inference engines.</li> <li>Strong network within the AI/ML research and engineering community.</li> <li>Genuine passion for AI safety, interpretability, and building systems that earn human trust.</li> </ul> <p><strong>Preferred Qualifications</strong></p> <ul> <li>Prior experience at a frontier AI lab or leading AI research organization.</li> <li>Experience shipping ML products to enterprise or research customers.</li> <li>Background in or familiarity with interpretability, alignment, or AI safety research.</li> <li>Public presence in the AI community (publications, open-source contributions, speaking engagements).</li> </ul> <h2>Our values</h2> <p>Goodfire is looking for individuals who embody our values and share our deep commitment to making interpretability accessible. We are building a team first and foremost.</p> <p><strong>Put mission and team first</strong></p> <p>All we do is in service of our mission. We trust each other, deeply care about the success of the organization, and choose to put our team above ourselves.</p> <p><strong>Improve constantly</strong></p> <p>We are constantly looking to improve every piece of the business. We proactively critique ourselves and others in a kind and thoughtful way that translates to practical improvements in the organization. We are pragmatic and consistently implement the obvious fixes that work.</p> <p><strong>Take ownership and initiative</strong></p> <p>There are no bystanders here. We proactively identify problems and take full responsibility over getting a strong result. We are self-driven, own our mistakes, and feel deep responsibility over what we’re building.</p> <p><strong>Action today</strong></p> <p>We have a small amount of time to do something incredibly hard and meaningful. The pace and intensity of the organization is high. If we can take action today or tomorrow, we will choose to do it today.</p> <h2>Where we work</h2> <p>We are hiring for this position in our San Francisco HQ. We are in person 5 days a week, with one company-wide remote week per month.</p> <h2><strong>What We Offer</strong></h2> <p>This role offers market competitive salary, equity, and compe