Goodfire is an AI interpretability research lab focused on understanding and intentionally designing advanced AI systems. Backed by Lightspeed, AI Grant and Menlo.
About the role
We're looking for Product Engineers to help build the core product experience for training, evaluating, debugging, and deploying interpretable AI systems at scale. You'll play a central role in turning Goodfire's research and platform capabilities into products that people can actually use: clear interfaces, reliable workflows, developer tools, and product surfaces that make model internals understandable and actionable.
What they're looking for
- 2+ years of experience building production software, especially user-facing products, data-intensive systems, or AI/ML products
- Strong engineering fundamentals and ability to work across the stack, with depth in at least one of frontend, backend, systems, or product infrastructure
- Strong product judgment, you care about making powerful technical systems feel clear, reliable, and easy to use
- Comfort working across research, engineering, design, and customer-facing teams
- You care about understanding how models work internally and using that understanding to make AI systems more reliable and useful in the real world
More about this role
Goodfire is an AI interpretability research lab. We build interpretability agents and infrastructure to understand, monitor, and align AI models.
We believe that AI is the most consequential technology of our time. Yet AI models are trained by trial and error today, with limited understanding of what drives their behavior. Our goal is to advance the research and technology needed to fully understand and align AI so humanity can trust superintelligence.
Goodfire is a public benefit corporation founded by researchers who helped pioneer the field of interpretability at OpenAI and Google DeepMind. We are headquartered in San Francisco and have raised over $200M from leading investors including Lightspeed, Menlo, and B Capital.
We're looking for Product Engineers to help build the core product experience for training, evaluating, debugging, and deploying interpretable AI systems at scale. You'll play a central role in turning Goodfire's research and platform capabilities into products that people can actually use: clear interfaces, reliable workflows, developer tools, and product surfaces that make model internals understandable and actionable.
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