Research Scientist, RSP Evaluations (CBRN, Biosecurity)

We’re building

a team that will research and mitigate extreme risks from future models .

This team will intensively red-team models to test the most significant risks they might be capable of in areas such as biosecurity, cybersecurity risks, or autonomy. We believe that clear demonstrations can significantly advance technical research and mitigations, as well as identify effective policy interventions to promote and incentivize safety.

As part of this team, you will lead research to baseline current models and test whether future frontier capabilities could cause significant harm. Day-to-day, you may decide you need to finetune a model to see whether it becomes superhuman in an eval you’ve designed; whiteboard a threat model with a national security expert; test a new training procedure or how a model uses a tool; or brief government, labs, and other research teams. Our goal is to see the frontier before we get there.

We’re currently hiring for our CBRN workstream, with an emphasis on

biosecurity risks (as outlined in our

Responsible Scaling Policy ). By nature, this team will be an unusual combination of backgrounds. We are particularly looking for people with experience in these domains:

Biosecurity:

You're a biologist who's concerned about the implications of AI development. You're an academic who researches biosecurity defense. You have experience modeling biological phenomena or developing advanced threat modeling simulations.

Science:

You’re an ML researcher who builds agents to augment chemistry or biology research. You’ve built a protein language model and you enjoyed looking through the embedding space. You’re a team lead at an ML-for-drug discovery company. You’ve built software for astronauts or materials scientists.

Evaluations:

You’ve managed a large-scale benchmark development project, in AI or other domains. You have ideas about how AI and ML evaluations can be better.

For this job posting, you can apply to one of two tracks: Research Scientist or Research Engineer.

Do not rule yourself out if you do not fit one of those categories - it’s plausible the people we’re looking for do not fit any of the above! If you think about the most significant upsides and downsides of AI, and you can do good research to get glimpses of what those look like, please consider applying.

Please note: We will only be considering candidates who can be based in the Bay Area for this role. We have a strong preference for candidates who can start ASAP, and ideally by February 2025.

Responsibilities

Independently lead small research projects while collaborating with team members on larger initiatives

Design, run, and analyze scientific experiments to advance our understanding of large language models

Work with external partners to develop novel evaluations to accurately assess the biosecurity implications of our models

For Research Scientists:

Synthesize biosecurity research to establish

thresholds of concern

for AI capabilities

Develop a framework for how we might assess the impact of AI on biosecurity

Communicate our findings to external stakeholders, such as policymakers

For Research Engineers:

Lead technical design discussions to ensure our infrastructure can support both current needs and future research directions

Interface with, and improve our internal technical infrastructure and tools

Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic’s safety mission

You may be a good fit if you

Have one of:

For the Research Scientist track: Advanced degree (MS or PhD) in the biological sciences (Molecular Biology, Computational Biology, Bioengineering) or 4+ years of professional experience in biology research (including wet-lab)

and

some familiarity with machine learning or software engineering (Python preferred)

For the Research Engineer track: Professional work experience in software engineering or machine learning

and

interest or past exposure to biosecurity

Take pride in writing clean, well-documented code in Python that others can build upon

Have a track record of using technical infrastructure to interface effectively with machine learning models

Have familiarity with prompting and engineering large language models

Are able to balance research goals with practical engineering constraints

Have strong problem-solving skills and a results-oriented mindset

Have excellent communication skills and ability to work in a collaborative environment

Pick up slack, even if it goes outside your job description

Prefer fast-moving collaborative projects to extensive solo efforts

Care about the societal impacts of AI

Strong candidates may also have experience with

Wet lab experience in molecular biology

Have previous experience leading large projects with multiple external collaborators or stakeholders

Previous experience with developing evaluations or benchmarks for large language models

Familiarity with GPUs, Kubernetes, and OS internals

Experience with language modeling using transformer architectures

Previous experience in emerging technology policy, including in biosecurity or AI

Representative projects

Design and implement a new evaluation to test models for CBRN risks

Manage a large-scale automated evaluations run across our clusters

Develop a detailed threat model of CBRN risks, and identify how core bottlenecks can be resolved from further evaluations

Prepare briefing materials to share the results of an evaluation run with external research groups

Candidates need not have

Previous professional experience in AI Safety

100% of the skills needed to perform the job

Deadline to apply: None. Applications will be reviewed on a rolling basis.

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