Job Details

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 Machine Learning Engineer (Life Sciences) to help build our platform for training, evaluating, and deploying interpretable frontier AI systems, with an emphasis on scientific and biological foundation models(e.g., genomic foundation models, protein language models, vision models for digital pathology).

Where you might contribute:

• Forward deployed research - lead scientific research with our partners to interpret advanced biological foundation models (genomic foundation models, ViTs, PLMs) to uncover what they've learned.
• Project delivery and implementation - own research delivery on high-stakes projects with customers and do whatever it takes to make delivery successful, including: problem and hypothesis definition, data sourcing, tool building, iteration, and implementation. Translate research into tools for real-world applications in precision medicine, digital pathology, drug discovery, and more.

Key responsibilities:

• Productionize interpretability research into maintainable tools, APIs, and workflows that work on real models and real scientific data.
• Optimize pipelines and infrastructure for frontier model interpretability, training, and inference.
• Prototype techniques to visualize and manipulate internal model structures.
• 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

• Experience with biological / life sciences ML (computational biology, bioinformatics, digital pathology, protein/genomics, multimodal biomedical data).
• Open-source ML infrastructure 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.
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 (depending on level and scope).

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.