Research Scientist, Life Sciences (Large Molecules, Process Development)

Excerpt from the original posting

About Anthropic 

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role

Anthropic's Life Sciences team is building a research group focused on biological discoveries by combining AI with hands-on biological research. We're seeking a research scientist with deep expertise in antibody process development and manufacturing to join the team. Our goal is to speed up progress in the life sciences by an order of magnitude, and this role puts that mission into practice. You'll be an expert in making antibodies, with hands-on experience expressing, purifying, characterizing, and formulating them, from small screening batches to material for IND-enabling studies. Above all, you'll close the loop between AI-generated hypotheses and experimental data to share with the community. Working alongside AI researchers and engineers, you'll build and run the workflows that turn AI-designed sequences into well-characterized protein, and pressure-test AI predictions of expression, stability, and manufacturability against real data.

This role is fully on-site in the San Francisco Bay Area.

Key responsibilities

- Develop and run expression and purification processes for antibodies and other recombinant proteins end to end, including transient and stable expression in mammalian cells (HEK293, CHO), affinity capture (Protein A, IMAC), polishing chromatography, buffer exchange, and formulation

- Characterize what we make with the right analytical panel, for example SEC, CE-SDS, icIEF, LC-MS (intact mass, peptide mapping, glycans), DLS, thermal stability, endotoxin, and binding kinetics (SPR, BLI)

- Build the laboratory for this work, including selecting, installing, and qualifying equipment and setting up workflows that scale from plate-based production of hundreds of designs to gram quantities of a lead

- Evaluate AI-designed antibodies for manufacturability (titer, aggregation, stability under stress, viscosity, chemical liabilities), drive them to experimental readout, and feed results back to research teams

- Plan the chemistry, manufacturing, and controls (CMC) path toward IND-enabling studies, from cell line development and scale-up to analytical methods and stability, and coordinate techno…

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