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

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 technology transfer and manufacturing with external contract manufacturers
• Ensure experimental data across programs is high quality and well documented, including batch records, methods, raw data, and failure modes
• Communicate findings clearly to biology, AI research, and life sciences audiences

Minimum qualifications

• PhD in biochemical engineering, chemical engineering, biochemistry, or a related field
• Demonstrated experience in process development and manufacturing of antibodies or other recombinant proteins, including material supplied for IND-enabling or clinical studies, with recent, sustained hands-on laboratory work
• Comfort navigating ambiguity and defining problems in a rapidly evolving research environment
• Ability to work independently while collaborating effectively across cross-functional teams, with strong written and verbal communication skills

Preferred qualifications

• 5+ years of biologics process development experience beyond the PhD
• Depth in both upstream (cell line development, bioreactors) and downstream (chromatography, filtration) development, with working knowledge of analytical and formulation development
• Experience setting up a protein production or process development laboratory, including laboratory automation and high-throughput, plate-based expression and purification
• Experience directing technology transfer and GMP manufacturing at contract development and manufacturing organizations, with contributions to the CMC sections of an IND
• Statistics or coding skills, for example design of experiments or Python for data analysis and automation
• Experience using AI or ML tools in the life sciences
• Publications and/or patents demonstrating scientific impact

The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary: $300,000 — $320,000 USD

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.