Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
Game Theory @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic’s AI & Rule of Law team researches how increasingly powerful AI systems may affect constitutional democratic institutions, including courts, legislatures, electoral systems, oversight bodies, and legal frameworks. The role focuses on early, high-stakes research into vulnerabilities and strategies for protecting democratic freedoms through technical and policy approaches.
Responsibilities
- Contribute to public data and research on how people use AI for politics, including reports and in-depth research on elections and policy topics.
- Design and conduct empirical research on AI’s political effects using external data sources and Anthropic’s privacy-preserving measurement systems.
- Design, run, and analyze experiments involving systems of many AI agents, including whether political-economy tools such as rules, monitoring, voting, and dispute resolution help agents govern themselves and remain under human oversight.
- Develop methodological approaches for studying AI’s impact on politics.
- Develop measurement and causal-inference tools to evaluate the downstream political consequences of Anthropic’s training, product, and policy decisions.
- Build and maintain relationships with academic institutions, policy think tanks, and research partners.
- Serve as the point of contact for external researchers using Anthropic data.
- Work cross-functionally with technical teams to improve measurement infrastructure and data collection.
- Translate research insights into recommendations for model training, product decisions, and policy discussions.
- Support external engagement through research publications, policy briefs, convenings, and presentations.
Requirements
- Primary degree in law, political science, or a closely related field at the Ph.D. level.
- Computational research background in political science, economics, or a related field.
- Demonstrated ability to produce rigorous, public-facing work, such as scholarship, policy analysis, government output, or a published body of writing.
Preferred Qualifications
- Experience studying AI’s impact on politics.
- Track record of empirical research, particularly research combining novel data sources with game theory or implementing advanced causal-inference methods.
- Ability to work autonomously in an environment where problems are new and processes are still being developed.
- At least five years of relevant experience in academia, industry, or government.
Compensation
- Annual salary: $295,000–$345,000 USD.
Work Policy and Benefits
- Hybrid policy requiring staff to work from an Anthropic office at least 25% of the time; some roles may require more office time.
- Visa sponsorship is available, subject to role and candidate eligibility.
- Benefits include competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration space.
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