Research Lead, Training
Goodfire
| Company | Goodfire |
| Category | Science & Research |
| Location | San Francisco |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Lead |
| Salary | Not stated by the employer |
| Posted | 16 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
About Goodfire
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. 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.
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.
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. About the role
We're hiring a Research Lead, Training to lead Goodfire's model training organization and define the research agenda behind how we train more capable, aligned, and interpretable AI systems, including exploring the research frontier of intentional design .
We’re looking for a senior research leader who can drive model training today while exploring the next generation of training methods, from interpretability-informed approaches to entirely new paradigms. You'll build, mentor, and grow a world-class team of researchers, set technical direction, and partner closely with scientific leadership to turn ambitious ideas into production systems and lasting research breakthroughs.
Key responsibilities:
Lead Goodfire’s training organization and manage a high-performing team from day one
Set direction for model training as Goodfire develops and deploys its own models
Drive execution on post-training and model improvement work, with accountability for shipping high-quality training outcomes
Define and lead a research agenda in intentional design, interpretability-informed training, and alignment
Partner with our Chief Scientist to shape priorities, balance research and delivery, and translate strategy into execution
Build the team over time, including hiring, mentoring, and creating strong technical and managerial foundations
What you’ll bring
Required experience and qualifications
Experience leading post-training, model training, or closely related efforts in a frontier AI environment
Track record of owning ambitious technical programs that combine research depth with executional rigor
Experience managing teams and operating effectively in fast-moving, high-expectation environments
Strong judgment on how to balance longer-term research bets with near-term product or model delivery
Interest in intentional design, alignment, and interpretability-informed training
Ability to work closely with senior scientific leadership while also independently setting direction and driving outcomes
Our values
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.
Put mission and team first
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.
Improve constantly
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.
Take ownership and initiative
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