Forward Deployed Research Scientist

Posted 22 Days Ago
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San Francisco, CA, USA
In-Office
220K-315K Annually
Entry level
Software • Generative AI
The Role
Conduct original interpretability research with customers, analyze advanced AI models, prototype techniques to visualize and manipulate model structures, and translate research into production-ready tools. Lead high-stakes project delivery by defining hypotheses, sourcing data, building tools, and iterating with engineering and customer partners. Help shape the company’s research direction while communicating complex technical concepts clearly.
Summary Generated by Built In
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 a Forward Deployed Research Scientist to join our team to work directly with customers to apply our interpretability platform to solve novel problems for our customers. You’ll work closely with a small, mission-driven team of scientists and engineers to conduct novel research, build practical tools, and push the field forward.

Where you might contribute:

  • Forward deployed research – lead research with our partners to interpret advanced models.
  • 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.

Key Responsibilities:

  • Work directly with customers to conduct original research in interpretability.
  • Prototype techniques to visualize and manipulate internal model structures.
  • Collaborate with engineering to turn research into production-ready tools.
  • Drive partnership success by collaborating closely with our customers and partners.
  • Help define and evolve our research direction.
What you’ll bringRequired experience
  • MS/PhD or equivalent experience in CS, with a strong ML background and experience in interpretability.
  • Deep familiarity with large models and a passion for understanding how they work.
  • Fluency in Python and ML frameworks such as PyTorch.
  • Strong writing and communication skills for explaining complex ideas.
  • Drive to move quickly and take ownership.
Preferred qualifications
  • Experience leading research in a forward deployed environment and in service of a customer’s requirements.
  • Experience in startup or fast-paced lab environments.
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 $220,000 - $315,000 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.

Skills Required

  • MS, PhD, or equivalent experience in Computer Science
  • Strong machine learning background
  • Experience in AI interpretability
  • Deep familiarity with large models
  • Fluency in Python
  • Experience with machine learning frameworks such as PyTorch
  • Strong writing and communication skills
  • Drive to move quickly and take ownership
  • Experience leading research in a forward-deployed environment serving customer requirements
  • Experience in startup or fast-paced laboratory environments
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The Company
HQ: San Francisco, CA
9 Employees
Year Founded: 2024

What We Do

Our mission is to advance humanity's understanding of AI by examining the inner workings of advanced AI models (or “AI Interpretability”). As a research-driven product organization, we bridge the gap between theoretical science and practical applications of interpretability. We're building critical infrastructure that empowers developers to understand, edit, and debug AI models at scale, ensuring the creation of safer and more reliable systems. Goodfire is a public benefit corporation headquartered in San Francisco.

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