Research Scientist, Societal Impacts
San Francisco, CAFull-TimeMid-levelResearch
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
- As a Societal Impacts research scientist on the Models Research Pod, you'll close the loop between observing Claude's behavior and improving it at the model level. You'll use observational tools like Clio to analyze real-world usage patterns and build evaluations that assess whether Claude provides safe responses aligned with its Constitution.
- Strong candidates will have experience with machine learning systems and a genuine interest in societal impacts research. You should be adaptable and excited to contribute to evolving team priorities rather than coming in with a fixed agenda. The role is highly cross-functional, with regular collaboration across the fine-tuning, safeguards, policy, and interpretability teams.
- We're hiring at both junior and senior levels. Senior researchers should be comfortable doing hands-on technical work alongside helping set research direction.
Responsibilities
- Using observational tools like Clio to analyze real-world usage patterns and surface insights about how people interact with Claude.
- Building and running evaluations to assess Claude's behavior across key dimensions of its Constitution, such as safety and quality of advice in high-stakes situations.
- Partnering closely with fine-tuning, safeguards, policy, and interpretability teams to translate research insights into model improvements.
- Generating insights about the societal impact of Anthropic's systems and using this understanding to inform company strategy, research priorities, and policy positions.
- Sharing your work through research publications and external presentations, and developing tools and frameworks that make AI systems more understandable to policymakers, academics, and civil society.
You may be a good fit if
- You have experience working with machine learning systems and are comfortable with technical infrastructure for interfacing with models.
- You have an interest in societal impacts research; prior experience in this area is a plus but not required.
- You're adaptable and collaborative, able to take direction and contribute to team priorities rather than needing to pursue a predetermined research agenda.
- You're skilled at writing up and communicating your results, even when they're null or unexpected.
- You find it exciting to partner with colleagues across teams on large-scale projects where the whole company contributes to building and analyzing AI systems.
- You have a background in machine learning, data science, or another technical field that involves generating insights from complex systems.
- You're passionate about translating research insights into actionable recommendations for improving AI systems and informing policy.
- For senior candidates: you're willing to do hands-on work while also helping shape research direction, and you may be interested in management opportunities down the line.
Some examples of our work
- Clio: A system for privacy-preserving insights into real-world AI use
- Values in the Wild
- How People Use Claude for Support, Advice, and Companionship
- Economic Index
- How AI is Transforming Work at Anthropic
- Education Report: How University Students Use Claude
- The Capacity for Moral Self-Correction in Large Language Models
- Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned
- Challenges in evaluating AI systems
- Towards Measuring the Representation of Subjective Global Opinions in Language Models
- Collective Constitutional AI: Aligning a Language Model with Public Input
- Clio: A system for privacy-preserving insights into real-world AI use
- Values in the Wild
- How People Use Claude for Support, Advice, and Companionship
- Economic Index
- How AI is Transforming Work at Anthropic
- Education Report: How University Students Use Claude
- The Capacity for Moral Self-Correction in Large Language Models
- Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned
- Challenges in evaluating AI systems
- Towards Measuring the Representation of Subjective Global Opinions in Language Models
- Collective Constitutional AI: Aligning a Language Model with Public Input
- 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.
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.
