Six Figure Work

Research Scientist, Life Sciences (Large Molecules, Antibody Design)

Anthropic

Company websiteanthropic.com (Anthropic, opens in new tab)

Base salary $300K  to $320K

Employer-published annual base salary, USD. Advertised base range in San Francisco, CA

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  • LocationSan Francisco, CA
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (3 h ago) · observed since

About this job

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 therapeutic antibodies 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 antibody design and engineering who has taken antibodies through the whole process, from target selection and lead optimization to candidate selection and 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 drive antibody programs end to end and pressure-test AI-designed antibodies against the bar a real drug candidate has to clear.

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

Key responsibilities

  • Design and engineer therapeutic antibodies and oversee programs end to end, including target and epitope selection, choice of format (IgG, Fab, scFv, VHH, bispecific), humanization, affinity maturation, Fc engineering, and candidate selection
  • Define the screening cascade for each program, from binding kinetics (SPR, BLI), epitope binning, and species cross-reactivity to cell-based functional assays and developability (expression, aggregation, polyreactivity, stability, viscosity, immunogenicity risk)
  • Plan the path from lead to IND-enabling studies, including in vivo pharmacology, pharmacokinetics, toxicology, and the handoff to process development and manufacturing
  • Coordinate antibody production, characterization, and in vitro and in vivo studies with external contract research organizations and academic partners
  • Evaluate AI-designed antibodies, drive them to experimental readout, and feed results back to research teams
  • Ensure experimental data across programs is high quality and well documented, including sequences, protocols, raw data, and failure modes
  • Communicate findings clearly to biology, AI research, and life sciences audiences

Minimum qualifications

  • PhD in biochemistry, protein engineering, immunology, molecular biology, or a related field
  • Demonstrated experience in therapeutic antibody discovery and engineering, including at least one antibody you helped take from discovery through candidate selection and IND-enabling studies
  • Working knowledge of what an antibody IND requires across pharmacology, pharmacokinetics, toxicology, and chemistry, manufacturing, and controls (CMC)
  • 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 therapeutic antibody experience beyond the PhD
  • Track record of advancing more than one antibody program into IND-enabling studies or the clinic, with contributions to pre-IND or IND documents
  • Hands-on experience with antibody expression, purification, and biophysical characterization
  • Experience directing antibody production, assays, and in vivo studies at contract research organizations
  • Structural biology, computational protein design, or coding skills, for example Python for sequence and assay data analysis or structure prediction and protein design tools
  • 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.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

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.

Source: Anthropic on Greenhouse · View original posting (opens in new tab)

Pay in context

This role's base floor ($300,000) is above 92% of the 1,730 Data & ML roles in California listed on this site; 13 others list the same floor. Their median floor is $184,000; the middle half runs from $154,150 to $224,000.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.

This range next to 6 other live Anthropic roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Anthropic roles with the nearest advertised base floor
RolePublished base
Research Scientist, Life Sciences (Large Molecules, Antibody Design) (this listing)$300K - $320K
Research Scientist, Life Sciences$300K - $320K
Senior Engineer, Bioinformatics$300K - $320K
Research Scientist, Life Sciences (Computational)$300K - $320K
Front End Engineer, Marketing$300K - $320K
Research Scientist, Life Sciences (Computational Chemistry)$300K - $320K
Research Scientist/Engineer, Biological Safety$300K - $405K

Same $100K to $400K scale as every card. All Anthropic roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-10-29
Where this pay comes from

Location as the employer wrote it: San Francisco, CA

USD 300,000 – 320,000 · interval unstated · pay_input_range · Annual Salary: · base family (R345 A1)

Method
Structured pay field published by the employer
Checked
Rule set
us-base-v2

The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.

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