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 Member of Technical Staff to join our Field Team and be the technical backbone of our customer engagements, the person who takes our interpretability platform and makes it work inside a partner's environment, end-to-end. This role demands strong engineering capability, the ability to learn new domains fast, the creativity to design solutions under real-world constraints, and the comfort to operate directly alongside customer engineering and research teams.
This is a hands-on, high-ownership role where you will be forward-deployed with our most strategic partners: writing production code, building integrations, running pilots, and owning technical delivery day-to-day.
This role turns frontier research into deployed reality. You will typically be working with deeply technical partners - Heads of AI, research teams, ML platform teams - across Life Sciences, Robotics and Vision, Language and Reasoning models, or new verticals, helping them integrate our platform into their model training stack.
Key responsibilities
- Own technical delivery for partner engagements: build production-grade integrations of Goodfire's platform into customer environments — from API integrations and custom pipelines to internal tooling and evaluation workflows
- Run pilots that prove value fast: design and execute creative, short-timeline pilots that demonstrate the platform's impact, often in parallel with or ahead of longer-term solution scoping
- Embed with partner engineering teams: serve as the day-to-day technical point of contact, going deep in their codebase, understanding their infrastructure, and building trust through competence
- Compound learnings across engagements: bring field insights back to the platform and research teams, identify repeatable patterns, and build shared tooling and playbooks that scale the Field Team
- Bridge research and production: take novel interpretability methods from the Foundational Team and figure out how to make them work reliably in a partner's stack — this means being comfortable reading papers, prototyping new techniques, and hardening them for production use
What you’ll bring
Required experience
- Strong software engineering skills with production experience in Python and modern ML frameworks (PyTorch, JAX).
- Ability to work across research and engineering boundaries - you can understand a new technique and figure out how to ship it.
- Scrappiness, willingness to persist in ambiguity, ability to learn quickly, and a generalist "can-do" mindset.
- Strong communication skills - you can explain technical tradeoffs clearly to both engineers and non-technical stakeholders.
Preferred qualifications
- Technical degree or equivalent professional experience within AI, ML, or a related field.
- Experience in a forward-deployed, solutions, or customer-facing engineering role. Former technical founders encouraged to apply.
- Track record of excellence in a high-growth startup or frontier AI lab.
- Experience with large language models, including fine-tuning, evaluation frameworks, or agent development.
- Familiarity with interpretability, mechanistic interpretability, or model internals (sparse autoencoders, feature steering, etc.).
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 our San Francisco HQ. 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 - $325,000 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.