Anthropic

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2><strong>About the role</strong></h2>
<p>As a Regional Research Economist at Anthropic, you will work to collaborate with governments, academia, industry, and civil society in your region to measure and understand AI's effects on the economy and explore research-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally-relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions.</p>
<p>Our team combines rigorous empirical methods with novel measurement approaches. We're building first-of-its-kind datasets tracking AI's impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system (<a href="https://www.anthropic.com/research/clio" rel="noopener noreferrer ugc" target="_blank">Clio</a>), we <a href="https://assets.anthropic.com/m/2e23255f1e84ca97/original/Economic_Tasks_AI_Paper.pdf" rel="noopener noreferrer ugc" target="_blank">analyze millions of real-world AI interactions</a> to understand how AI augments and automates work across different occupations and tasks.</p>
<h2><strong>Key responsibilities</strong></h2>
<ul>
<li>Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region</li>
<li>Advance research collaborations that answer country- or regional-specific economic impact questions</li>
<li>Translate research insights into actionable recommendations for policy discussions</li>
<li>Make fundamental contributions to the development and expansion of the <a href="https://www.anthropic.com/economic-index" rel="noopener noreferrer ugc" target="_blank">Anthropic Economic Index</a>, including country/regional-specific analysis</li>
<li>Design and collaborate on empirical research on AI's economic effects with governments, academia, industry, and civil society in your region</li>
<li>Develop new methodological approaches, in collaboration with partners in your region, for studying AI's impact on:</li>
<ul>
<li>Labor markets and the future of work</li>
<li>Productivity and task transformation</li>
<li>Economic inequality and displacement</li>
<li>Industry-specific disruption and adaptation</li>
<li>Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios</li>
</ul>
<li>Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection</li>
<li>Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders</li>
</ul>
<h2><strong>Minimum qualifications</strong></h2>
<ul>
<li>PhD in Economics</li>
<li>Strong track record of empirical research, particularly studies combining novel data sources and economic theory or those implementing frontier methods in causal inference and machine learning</li>
<li>Demonstrated experience working in and relevant relationships across the region</li>
<li>Experience relevant to the study of AI’s impact on the economy, including:</li>
<ul>
<li>Labor market analysis and occupational change</li>
<li>Task-based approaches to technological transformation</li>
<li>Large-scale data analysis and econometric methods</li>
<li>Large language models for social science research</li>
<li>Policy-relevant economic research</li>
<li>Experimental and quasi-experimental methods for causal inference</li>
<li>Macroeconomic modeling and time series forecasting</li>
<li>Agent-based modeling or large-scale simulation</li>
</ul>
<li>Technical skills including:</li>
<ul>
<li>Proficiency in Python, R, SQL, or similar tools for large-scale data analysis</li>
<li>Experience working with novel datasets and measurement systems</li>
<li>Comfort learning new technical tools and frameworks</li>
</ul>
<li>Demonstrated ability to:</li>
<ul>
<li>Lead complex research projects from conception to publication</li>
<li>Communicate technical findings to diverse audiences</li>
<li>Build relationships across academic, policy, and industry communities</li>
</ul>
<li>Strong interest in ensuring AI development benefits humanity</li>
<li>Comfort working with AI systems and ability to think critically about their capabilities and limitations</li>
</ul>
<h2><strong>Representative projects</strong></h2>
<ul>
<li><a href="https://www.anthropic.com/research/how-australia-uses-claude" rel="noopener noreferrer ugc" target="_blank">How Australia Uses Claude: Findings from the Anthropic Economic Index</a></li>
<li><a href="https://www.anthropic.com/research/anthropic-economic-index-january-2026-report" rel="noopener noreferrer ugc" target="_blank">Anthropic Economic Index Report: Economic Primitives</a></li>
<li><a href="https://www.anthropic.com/research/anthropic-economic-index-september-2025-report" rel="noopener noreferrer ugc" target="_blank">Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption</a></li>
<li><a href="https://www.anthropic.com/research/estimating-productivity-gains" rel="noopener noreferrer ugc" target="_blank">Estimating AI productivity gains from Claude conversations</a></li>
<li><a href="https://www.anthropic.com/economic-index" rel="noopener noreferrer ugc" target="_blank">The Anthropic Economic Index</a></li>
</ul>
<h2><strong>Additional information</strong></h2>
<p>For this role, we're looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI's transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact.</p><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

Regional Research Economist, Economic Research

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2><strong>About the Role</strong></h2>
<p>As a Regional Research Economist at Anthropic, you will work to collaborate with governments, academia, industry, and civil society in your region to measure and understand AI's effects on the economy and explore research-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally-relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions.</p>
<p>Our team combines rigorous empirical methods with novel measurement approaches. We're building first-of-its-kind datasets tracking AI's impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system (<a href="https://www.anthropic.com/research/clio" rel="noopener noreferrer ugc" target="_blank">Clio</a>), we <a href="https://assets.anthropic.com/m/2e23255f1e84ca97/original/Economic_Tasks_AI_Paper.pdf" rel="noopener noreferrer ugc" target="_blank">analyze millions of real-world AI interactions</a> to understand how AI augments and automates work across different occupations and tasks.</p>
<h2><strong>Key responsibilities</strong></h2>
<ul>
<li>Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region</li>
<li>Advance research collaborations that answer country- or regional-specific economic impact questions</li>
<li>Translate research insights into actionable recommendations for policy discussions</li>
<li>Make fundamental contributions to the development and expansion of the <a href="https://www.anthropic.com/economic-index" rel="noopener noreferrer ugc" target="_blank">Anthropic Economic Index</a>, including country/regional-specific analysis</li>
<li>Design and collaborate on empirical research on AI's economic effects with governments, academia, industry, and civil society in your region</li>
<li>Develop new methodological approaches, in collaboration with partners in your region, for studying AI's impact on:</li>
<ul>
<li>Labor markets and the future of work</li>
<li>Productivity and task transformation</li>
<li>Economic inequality and displacement</li>
<li>Industry-specific disruption and adaptation</li>
<li>Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios</li>
</ul>
<li>Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection</li>
<li>Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders</li>
</ul>
<h2><strong>Minimum qualifications</strong></h2>
<ul>
<li>PhD in Economics</li>
<li>Strong track record of empirical research, particularly studies combining novel data sources and economic theory or those implementing frontier methods in causal inference and machine learning</li>
<li>Demonstrated experience working in and relevant relationships across the region</li>
<li>Experience relevant to the study of AI’s impact on the economy, including:</li>
<ul>
<li>Labor market analysis and occupational change</li>
<li>Task-based approaches to technological transformation</li>
<li>Large-scale data analysis and econometric methods</li>
<li>Large language models for social science research</li>
<li>Policy-relevant economic research</li>
<li>Experimental and quasi-experimental methods for causal inference</li>
<li>Macroeconomic modeling and time series forecasting</li>
<li>Agent-based modeling or large-scale simulation</li>
</ul>
<li>Technical skills including:</li>
<ul>
<li>Proficiency in Python, R, SQL, or similar tools for large-scale data analysis</li>
<li>Experience working with novel datasets and measurement systems</li>
<li>Comfort learning new technical tools and frameworks</li>
</ul>
<li>Demonstrated ability to:</li>
<ul>
<li>Lead complex research projects from conception to publication</li>
<li>Communicate technical findings to diverse audiences</li>
<li>Build relationships across academic, policy, and industry communities</li>
</ul>
<li>Strong interest in ensuring AI development benefits humanity</li>
<li>Comfort working with AI systems and ability to think critically about their capabilities and limitations</li>
</ul>
<h2><strong>Representative projects</strong></h2>
<ul>
<li><a href="https://www.anthropic.com/research/how-australia-uses-claude" rel="noopener noreferrer ugc" target="_blank">How Australia Uses Claude: Findings from the Anthropic Economic Index</a></li>
<li><a href="https://www.anthropic.com/research/anthropic-economic-index-january-2026-report" rel="noopener noreferrer ugc" target="_blank">Anthropic Economic Index Report: Economic Primitives</a></li>
<li><a href="https://www.anthropic.com/research/anthropic-economic-index-september-2025-report" rel="noopener noreferrer ugc" target="_blank">Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption</a></li>
<li><a href="https://www.anthropic.com/research/estimating-productivity-gains" rel="noopener noreferrer ugc" target="_blank">Estimating AI productivity gains from Claude conversations</a></li>
<li><a href="https://www.anthropic.com/economic-index" rel="noopener noreferrer ugc" target="_blank">The Anthropic Economic Index</a></li>
</ul>
<h2><strong>Additional Information</strong></h2>
<p>For this role, we're looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI's transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact.</p><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>£195,000</span><span>—</span><span>£245,000 GBP</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2><strong>About the role</strong></h2>
<p>As part of our growing Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You’ve worked in cultures of excellence in the past, and are eager to apply that experience to help shape the cultural norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world.</p>
<p><strong>Responsibilities:</strong></p>
<ul>
<li>Deep dive into product and user data to derive actionable insights and size opportunities to improve products, strategy and operations, influencing roadmaps through your insights and recommendations</li>
<li>Develop hypotheses, apply rigorous causal inference methods – controlled experiments, synthetic controls –  and analyze the results in order make actionable recommendations </li>
<li>Investigate anomalies, conduct root cause analyses, and provide data-driven insights to guide priorities and inform decisions</li>
<li>Define core metrics, build measurement frameworks, and maintain core reporting to evaluate success</li>
<li>Build statistical models, optimization frameworks, and simulations to automate decision-making and operational processes</li>
<li>Present complex technical analyses and recommendations to both technical and non-technical stakeholders</li>
<li>Establish foundational data practices and help scale our analytics infrastructure to support rapid iteration and decision-making as our products grow</li>
</ul>
<p><strong>You may be a good fit if you have:</strong></p>
<ul>
<li>7+ years of experience in data science or analytics roles </li>
<li>Deep expertise with Python, SQL, and data visualization tools</li>
<li>Expertise with experimental design, causal inference, statistical modeling, and A/B testing frameworks, particularly in high-scale technical environments</li>
<li>Highly effective written communication and presentation skills</li>
<li>A track record of translating complex data into clear, actionable insights for both technical and business stakeholders</li>
<li>A bias for action and ability to thrive in ambiguous, fast-moving environments where you must create clarity and drive forward progress</li>
<li>A passion for the company’s mission of building helpful, honest, and harmless AI</li>
<li>Some experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem</li>
</ul><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>$285,000</span><span>—</span><span>$380,000 USD</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

Data Scientist, Product

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2>About the role</h2>
<p>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.</p>
<p> </p>
<p>We're hiring at both junior and senior levels. Senior researchers should be comfortable doing hands-on technical work alongside setting research direction.</p>
<h2>Responsibilities</h2>
<ul>
<li>
<p>Identify the signals that track AI R&amp;D acceleration and design the evaluations that measure them</p>
</li>
<li>
<p>Build quantitative models of capability growth and self-improvement dynamics, grounded in evaluation and telemetry data</p>
</li>
<li>
<p>Run experiments and evals to test hypotheses about automation and capability</p>
</li>
<li>
<p>Make opinionated research bets and own the outcome</p>
</li>
<li>
<p>Write graded assessments of what our measurements show, for internal decision-makers and public reporting</p>
</li>
<li>
<p>Collaborate with pretraining, RL, economic research, and policy teams</p>
</li>
</ul>
<h2>You may be a good fit if you</h2>
<ul>
<li>
<p>Have done hands-on research on large language models: pretraining, fine-tuning, RL, evals, or agent systems</p>
</li>
<li>
<p>Have strong quantitative instincts, are comfortable with quantitative modeling and reasoning</p>
</li>
<li>
<p>Have experience in forecasting, may have published AI forecasting scenarios</p>
</li>
<li>
<p>Can design an evaluation from a vague question and defend the methodology</p>
</li>
<li>
<p>Write clearly and calibrate: state confidence, name what would change your conclusion</p>
</li>
<li>
<p>Are motivated by impact: comfortable with work whose output is graded assessments and system-card sections more often than papers</p>
</li>
<li>
<p>Care about AI safety and think carefully about where rapid capability growth leads</p>
</li>
</ul>
<h2>Strong candidates may also have</h2>
<ul>
<li>
<p>Trained or RL'd frontier models hands-on</p>
</li>
<li>
<p>Experience with scaling laws, capability forecasting, or emergent-capability studies</p>
</li>
<li>
<p>A physics, applied-math, or similarly quantitative background that moved into ML</p>
</li>
<li>
<p>Written a system card section, capability report, or methodology document that others cite</p>
</li>
<li>
<p>Experience supervising and correcting AI-written code</p>
</li>
</ul>
<h2>Some examples of our work</h2>
<ul>
<li>
<p>Anthropic ECI:  our adaptation of Epoch Capabilities Index published in all recent system cards to measure capability acceleration</p>
</li>
<li>
<p>AI R&amp;D capability assessments in the Claude system cards</p>
</li>
<li>
<p><a href="https://www.anthropic.com/institute/recursive-self-improvement" target="_blank" rel="noopener noreferrer ugc">When AI Builds Itself</a>: all data in the article comes from our team</p>
</li>
</ul><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>$350,000</span><span>—</span><span>$850,000 USD</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

Research Scientist, Takeoff Intel

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2><strong>About the role</strong></h2>
<p>Anthropic's Safeguards team builds the systems that detect and mitigate misuse of our AI models, from individual policy violations to sophisticated, coordinated attacks. A growing part of that work depends on lightweight detection methods trained on model internals, which let us identify harmful behavior cheaply and at scale. This work feeds directly into Anthropic's Responsible Scaling Policy commitments.</p>
<p>We're looking for an engineer to own the infrastructure behind that research. This is the tooling our researchers rely on to run experiments, train detection methods, and select detections for launch. It sits between research and production: researchers depend on it for fast iteration, and our detection systems depend on it for reliable, correct results as our models continue to change.</p>
<p>Running machine learning workloads at our scale often requires solving novel systems problems. You'll identify those problems and build the abstractions, pipelines, and tooling that keep the research loop fast as requirements shift underneath you. Strong candidates will have a track record of solving large-scale systems and data problems and will be excited to grow deep machine learning expertise alongside it.</p>
<h2><strong>Key responsibilities</strong></h2>
<ul>
<li>Build and scale the infrastructure and data pipelines behind Safeguards machine learning research</li>
<li>Own the training, evaluation, and scoring workflows researchers use, with a focus on cutting the time between an idea and a result</li>
<li>Design tooling and interfaces, including libraries and command line tools, that researchers can use directly without needing to understand the systems underneath</li>
<li>Build correctness and sanity checking into the stack, so results stay trustworthy as models and workloads evolve</li>
<li>Take the highest-value research workflows from experiments to reliable, production-grade jobs</li>
<li>Improve the throughput, cost, and reliability of large-scale inference and scoring workloads</li>
<li>Partner closely with researchers and engineers across Safeguards to understand their workflows, anticipate how their needs will change, and design for that ahead of time</li>
</ul>
<h2><strong>Minimum qualifications</strong></h2>
<ul>
<li>Strong software engineering fundamentals and hands-on coding ability, with proficiency in Python</li>
<li>Experience building and operating data-intensive or distributed systems in production</li>
<li>Experience building tooling or infrastructure that other engineers or researchers use as a dependency</li>
<li>Comfort working across the research-to-deployment pipeline, from exploratory experiments to production systems</li>
<li>Ability to debug performance and correctness problems across an unfamiliar stack</li>
<li>Strong written and verbal communication skills, and a collaborative approach to technical decisions</li>
</ul>
<h2><strong>Preferred qualifications</strong></h2>
<ul>
<li>Experience with high-performance, large-scale machine learning systems</li>
<li>Familiarity with language modeling and transformers, including working with model internals</li>
<li>Experience with machine learning framework internals, GPU or accelerator programming, or inference optimization</li>
<li>Experience building experiment tracking, caching layers, or evaluation harnesses for research teams</li>
<li>Experience with probes, interpretability, or classifier development</li>
<li>Interest in the misuse risks of AI systems and a desire to work on mitigating them</li>
</ul><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>$350,000</span><span>—</span><span>$500,000 USD</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

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