Sobre el puesto
About Goodfire
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.
About the role
We’re looking for Machine Learning Engineers to help build our platform for training, evaluating, and deploying interpretable AI systems at scale. You’ll play a central role in building our core technology, from training and eval tooling to product features, to achieve our mission of understanding and intentionally designing AIs.
Where you might contribute:
• Interpretability tools – Building the tools and infrastructure to support understanding and intentional design of models at industry scale.
• Training infrastructure – Extending and supporting our training infrastructure for large training runs.
• Product – Turning state of the art interpretability research into robust, usable product features.
We'll work with you to determine the team that best aligns with your strengths.
Key responsibilities:
• Turn cutting edge interpretability research into production ready tools.
• Optimize pipelines and infrastructure for frontier model interpretability, training, and inference.
• Integrate new machine learning workflows and pipelines into our product and deploy to customers.
• Ensure system reliability, reproducibility, and performance.
What you’ll bring
Required experience
• 5+ years of experience in ML infra, research engineering, or systems programming.
• Comfort working across research and engineering boundaries.
• Expertise in Python, PyTorch or Jax, and distributed systems.
• Experience deploying and maintaining ML systems at scale.
• You care about understanding how models work internally and using that to make them more reliable and useful in the real world.
Preferred qualifications
• Open-source ML infra contributions.
• Startup or frontier lab experience in fast-moving teams.
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
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.
Action today
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.
Where we work
We are hiring for this position in both our San Francisco HQ and our New York office. We are in person 5 days a week, with one company-wide remote week per month.
What we offer
This role offers market competitive salary, equity, and competitive benefits.
The expected salary range for this position is $200,000 - $400,000 USD
Most importantly, you'll have the opportunity to join a vital mission at an important point in its trajectory — we are developing groundbreaking technology with a world-class team on the critical path to ensuring a safe and beneficial future for humanity. If you want to do your life’s work with us, even if you believe you do not meet every single requirement, apply now.
Publicada el 4 dic 2025
