Forward Deployed Research Scientist, Life Sciences
AI summary of the role
Goodfire is hiring a Forward Deployed Research Scientist (Biology) to work directly with customers on interpreting and steering large biological foundation models (genomic, vision, protein language models).
What you’ll do
- Lead scientific research with partners to interpret advanced biological foundation models (genomic foundation models, ViTs, PLMs).
- Own research delivery on high-stakes customer projects from hypothesis definition through implementation.
- Prototype techniques to visualize and manipulate internal model structures.
- Collaborate with engineering to turn research into production-ready tools.
What you’ll bring
- PhD/MD or equivalent experience in biology with strong ML background and computational biology or bioinformatics experience.
- 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.
Technologies
PyTorch · Python · genomic foundation models · ViTs · PLMs · interpretability · computational biology · bioinformatics
About Goodfire AI
Public benefit AI lab building Ember, an interpretability platform that decodes and steers neural network internals for alignment, debugging, and scientific discovery.
Series B · 50–100 people
Source and classification
Implementation & delivery · Evidence for this classification:
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 Scientific AI models trained to model natural systems are revolutionizing research across scientific domains, including protein interaction prediction, protein design, disease prediction, and materials discovery. We’re looking for a Forward Deployed Research Scientist (Biology) to join our team to work directly with customers to develop new techniques for understanding and designing large biological foundation models. 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
More from the job description
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 Scientific AI models trained to model natural systems are revolutionizing research across scientific domains, including protein interaction prediction, protein design, disease predic [... source excerpt omitted ...] oundation 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: Work directly with customers to conduct original research in interpretability and computational biology. Prototype techniques to visualize and manipulate internal model structures. Coll [... source excerpt omitted ...] 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. Familiarity with interpretability, alignment, or safe model development. 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 e
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