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 believe that learning is fundamental to human agency. Education Labs studies how people learn and build capability with AI, and we close the loop between what we discover and learning tools the world can access.
As our first dedicated education researcher, you will strengthen how the team measures learning and AI fluency so our experiments produce trustworthy evidence. You will design the instruments, build the tools, run the studies, and translate findings into changes across our product experiments and action research in real learning settings. You operate at the frontier where the right measures often do not exist yet and have to be built.
This is a hands-on research role embedded in a small team. You will publish and influence thinking across Anthropic, and you will also help decide what is working well enough to scale, what should be handed off to another team, and what should be spun down. We care about learning experiences that make people progressively more capable, curious, and empowered over time.
Responsibilities
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Design and run mixed-methods studies on how people develop real skill with AI, measuring success by capability growth rather than engagement.
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Build and validate the instruments, measures, and evaluation methods the team relies on, so that findings hold up to scrutiny and can be trusted by research, product and policy partners.
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Translate research insights into shipped product, curriculum, and model-level improvements through close collaboration with engineers, designers, and researchers.
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Generate net-new insights about how AI is reshaping learning, and how communities and organizations can organize to learn alongside it.
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Communicate your work through clear writing, prototypes, and presentations that shape thinking across the organization.
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Create tools using code and software to collect validated metrics at scale.
You may be a good fit if you have
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A research background in learning sciences, education, cognitive science, HCI, educational psychology, or a closely related field, whether formal or self-directed.
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Strong mixed-methods skills: experimental design, measurement and psychometrics, qualitative methods, and the judgment to choose the right approach for the question.
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Hands-on technical skill in Python, data analysis, and working with LLMs, enough to run your own analyses and prototype new measures.
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Comfort deriving insight from imperfect, dynamically changing data, and comfort making research decisions with incomplete information while holding a high bar.
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Comfort with ambiguity and undefined problem spaces, plus a bias toward rapid, iterative inquiry and quick learning loops.
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Clear communication and a track record of cross-functional collaboration with product, design, engineering, and research partners.
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Genuine curiosity about how AI is changing how people learn, work, and build capability, and a strong perspective on technology enhancing human capability rather than diminishing it.
Strong candidates may also have
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Experience measuring capability or skill development in production, including experimentation frameworks and A/B testing.
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Experience building simple tools or interfaces that let non-technical collaborators evaluate or learn from AI systems.
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Published writing, talks, or open work on skill development, human-AI interaction, or the learning sciences.
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Experience in learning platforms, developer tools, creative tools, or other products where mastery matters more than engagement.
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A point of view on how human relatedness and social connection shape learning, and why they matter as people learn alongside AI.
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Previous experience in research labs, frontier tech companies, or startups with high autonomy and ambiguity.
What this role is not
This is a hands-on research role embedded in a small team that builds and ships, not a standalone academic post. You will publish and influence, but you will also work shoulder to shoulder with engineers and designers to get measures and features into the hands of real learners. The role does not involve people management at the outset. If you are looking to immediately move into research management or lead a large team, this likely is not the right fit.
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—$405,000 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.
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, Multimoda
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