Research Scientist, Takeoff Intel

Anthropic Limited; San Francisco (CA); Hybrid; USD 350,000 - 850,000; Full time

Job summary

Anthropic is seeking a Research Scientist to measure and understand recursive-self-improvement in large models. You will design evaluations and models, run experiments, and interpret results to guide research direction.

We hire at junior and senior levels; seniors lead hands-on work while shaping research direction. Location-based hybrid policy applies; office presence is expected at least 25% of the time in our San Francisco area offices.

Qualifications

• Hands-on research experience with large language models (pretraining, fine-tuning, RL, evals, or agent systems).
• Strong quantitative instincts and ability to build and reason about models and signals.
• Ability to forecast and present eval results clearly.

Responsibilities

• Identify signals that track AI R&D acceleration and design evaluations.
• Build quantitative models of capability growth and self-improvement dynamics.
• Run experiments and evals to test hypotheses about automation and capability.
• Document measurements for internal decision-makers and public reporting.
• Collaborate with teams across pretraining, RL, economics, and policy.

Skills

Large language models

Quantitative modeling

Forecasting

Research design

Education

Bachelor's degree or equivalent

Tools

Python

Job description

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

We're looking for a Research Scientist who has done hands-on research on large models (pretraining, fine-tuning, RL, evals, or agents scaffolds) and wants to focus on measuring and understanding recursive-self-improvement. You know what the model-development loop looks like from the inside: which signals matter and where the real bottlenecks are. On this team you'll use that judgment to decide what's worth measuring, design the evaluations and models that measure it, and interpret what the results mean for how fast this is moving.

We're hiring at both junior and senior levels. Senior researchers should be comfortable doing hands-on technical work alongside setting research direction.

Responsibilities

Identify the signals that track AI R&D acceleration and design the evaluations that measure them

Build quantitative models of capability growth and self-improvement dynamics, grounded in evaluation and telemetry data

Run experiments and evals to test hypotheses about automation and capability

Make opinionated research bets and own the outcome

Write graded assessments of what our measurements show, for internal decision-makers and public reporting

Collaborate with pretraining, RL, economic research, and policy teams

You may be a good fit if you

Have done hands-on research on large language models: pretraining, fine-tuning, RL, evals, or agent systems

Have strong quantitative instincts, are comfortable with quantitative modeling and reasoning

Have experience in forecasting, may have published AI forecasting scenarios

Can design an evaluation from a vague question and defend the methodology

Write clearly and calibrate: state confidence, name what would change your conclusion

Are motivated by impact: comfortable with work whose output is graded assessments and system-card sections more often than papers

Care about AI safety and think carefully about where rapid capability growth leads

Strong candidates may also have

Trained or RL'd frontier models hands-on

Experience with scaling laws, capability forecasting, or emergent-capability studies

A physics, applied-math, or similarly quantitative background that moved into ML

Written a system card section, capability report, or methodology document that others cite

Experience supervising and correcting AI-written code

Some examples of our work

Anthropic ECI: our adaptation of Epoch Capabilities Index published in all recent system cards to measure capability acceleration

AI R&D capability assessments in the Claude system cards

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.

$350,000 - $850,000 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.

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.

Guidance on Candidates' AI Usage: Learn aboutour policy for using AI in our application process.

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 aboutour policy for using AI in our application process.

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