Machine Learning Engineer

Behind our name : Like fire, AI holds the potential for both immense benefit and significant risk. Just as mastering fire transformed human history, we believe the safe and intentional development of AI will shape the future of our species. Our goal is to tame this new fire.

Goodfire is an AI interpretability research company focused onunderstanding and designing AI systems that people can trust. Our mission is to advance humanity's understanding of AI to build safe and powerful AI systems. We believe that deep research breakthroughs are necessary to make this possible.

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’ve raised $59M from investors like Menlo, Lightspeed and Anthropic and work with customers including Arc Institute, Mayo Clinic, and Rakuten.

About the role

We’re looking for Machine Learning Engineers to help build our platform for training, evaluating, and deploying interpretable frontier AI systems. 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 designing the next generation of AI systems.

Where you might contribute :

Interpretability tools

– Building the tools and infrastructure to support dissection and design of models at frontier 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

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.

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.

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