Member of Technical Staff (Research Scientist)
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Before you apply
SalaryNo pay range posted
LocationSan Francisco
Work modeon-site
Typefull-time
SeniorityLead
DepartmentTechnical Staff
EquityIncluded
Company size11–50 people
PostedJul 7, 2026 · 4mo ago
Verified live3d ago
May no longer be actively hiring
Posted by the company on Jul 7, 2026No pay range listed, though California requires one
At a glanceSummarised by Seekless from the posting.
Track record of original research (first-author work at NeurIPS, ICML, ICLR, AISTATS, JMLR, TMLR, other top conferences/journals, impactful open models, or comparable research output)
Deep command of modern deep learning: generative models, architectures, optimization, and scaling
Drive a research agenda independently, from idea to experiment to result
High-agency, in person, and comfortable with the ambiguity of frontier research
Range across subfields — a strong researcher who picks up new domains fast, or meaningful time in an ML-for-something domain (robotics, biology, physics)
Widely-used open-source models or research artifacts
Familiarity with the protein-ML landscape
Interest in biology, protein design, and AI for science
Skills
Python
diffusion
autoregressive
NeurIPS
ICML
ICLR
AISTATS
JMLR
TMLR
About Anthrogen
Anthrogen is engineering post-modality biology. Today’s modalities reflect historical contingencies in biological progress, not fundamental categories. We develop the AI systems that design modular biological machines — and the experimental infrastructure to instantiate them. We’re a small, high-density team in San Francisco building frontier AI and the biological systems to validate it, and we care most about people who move fast, go deep, and pick up whatever the problem needs.
The role
We want researchers with great intuition in machine learning and solid fundamentals —irrespective of bio background. You’ll drive original research on the architectures, training objectives, and scaling behind our models, owning an agenda from idea to result. We’re a small, high-density team building frontier AI and the biological systems to validate it, and we index on research taste and output, not credentials.
What you’ll do
•
Push on generative models (diffusion, autoregressive), architectures, optimization, and scaling.
•
Turn research directions into models that work, in close collaboration with our engineering team.
•
Help define what frontier AI for biology looks like.
Who you are
•
You have a track record of original research (first-author work at NeurIPS, ICML, ICLR, AISTATS, JMLR, TMLR, other top conferences/journals, impactful open models, or comparable research output).
•
Deep command of modern deep learning: generative models, architectures, optimization, and scaling.
•
You drive a research agenda independently, from idea to experiment to result.
•
High-agency, in person, and comfortable with the ambiguity of frontier research.
Bonus points
•
Range across subfields — a strong researcher who picks up new domains fast, or meaningful time in an ML-for-something domain (robotics, biology, physics).
•
Widely-used open-source models or research artifacts.
•
Familiarity with the protein-ML landscape.
•
Interest in biology, protein design, and AI for science.
Logistics
Full-time, onsite in San Francisco.
Benefits
Equity: 0.05-0.5%.