Research Scientist

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 looking for a Research Scientist to join our team and develop new techniques for understanding and steering large AI models. You’ll work closely with a small, mission-driven team of scientists and engineers to conduct novel research, build practical tools, and push the field forward.

Where you might contribute:

• Interpretability mechanisms – Foundational research on how models represent and process information.
• Moonshots – High-upside bets on novel techniques that could unlock breakthroughs in model understanding.
• Applied research & usability – Translating research into tools for real-world users and enterprise applications.

We’ll determine your pod placement during the interview process based on your background and interests.

Key responsibilities:

• Conduct original research in interpretability and related fields.
• Prototype techniques to visualize and manipulate internal model structures.
• Collaborate with engineering to turn research into production-ready tools.
• Share your work through publications, demos, and open-source contributions.
• Help define and evolve our research direction.

What you’ll bring

Required experience

• PhD or equivalent experience in ML, computer science, or a quantitative science.
• Deep familiarity with large models and a passion for understanding how they work.
• Fluency in Python and ML frameworks such as PyTorch.
• Strong writing and communication skills for explaining complex ideas.
• Drive to move quickly and take ownership.

Preferred qualifications

• Experience leading research or contributing to open-source codebases.
• Familiarity with interpretability, alignment, or safe model development.
• Experience in startup or fast-paced lab environments.

Where we work

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.