Member of Technical Staff (Research Scientist)

Anthrogen; San Francisco (CA); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Equity 0.05-0.5%

Job summary

Anthrogen is a San Francisco–based startup engineering post-modality biology with frontier AI. We seek researchers who combine strong intuition in machine learning with solid fundamentals, regardless of biology background.

You’ll drive original research from idea to result and own an agenda for models and objectives. We are a small, high-density team building frontier AI and biological systems to validate it, prioritizing research taste and output over credentials.

Qualifications

• Track record of original research (first-author papers or comparable output).
• Deep command of modern deep learning: generative models, architectures, optimization, and scaling.
• Ability to drive a research agenda from idea to result independently.
• High-agency and comfortable with ambiguity of frontier research.

Responsibilities

• Push on generative models, architectures, optimization, and scaling.
• Turn research directions into models that work, in collaboration with engineering.
• Help define what frontier AI for biology looks like.

Skills

Original research

Deep learning

Generative models

Model optimization

Research independence

Job description

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.

Equity: 0.05-0.5%.