Anthropic
Research Scientist, Interpretability
Anthropic, San Francisco, California, United States, 94199
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Research Scientist, Interpretability
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Anthropic 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 When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. We’re looking for researchers and engineers to join our efforts.
People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Think of us as doing the "biology" or "neuroscience" of neural networks using microscopes we build, or treating neural networks as binary computer programs we are trying to reverse engineer.
For an overview of our work, see our research lead's introduction to Interpretability, the Hard Fork podcast episode, and our recent blog post with accompanying video. Some of our notable publications include "A Mathematical Framework for Transformer Circuits", "In-context Learning and Induction Heads", "Toy Models of Superposition", "Scaling Monosemanticity", and our Circuits’ Methods and Biology papers.
Responsibilities
Develop methods for understanding LLMs by reverse engineering algorithms learned in their weights
Design and run robust experiments, both quickly in toy scenarios and at scale in large models
Create and analyze new interpretability features and circuits to better understand how models work
Build infrastructure for running experiments and visualizing results
Work with colleagues to communicate results internally and publicly
You May Be a Good Fit If You
Have a strong track record of scientific research (in any field), and have done some work on Interpretability
Enjoy team science – working collaboratively to make big discoveries
Are comfortable with messy experimental science. We're inventing the field as we work, and the first textbook is years away
You view research and engineering as two sides of the same coin. Every team member writes code, designs and runs experiments, and interprets results
You can clearly articulate and discuss the motivations behind your work, and teach us about what you've learned. You like writing up and communicating your results, even when they're null
To learn more about the skills we look for and how to prepare for this role, see our blog post – "So You Want to Work in Mechanistic Interpretability?"
Familiarity with Python is required for this role.
Role Specific Location Policy This role is based in San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis.
Annual Salary $315,000—$560,000 USD
Education Requirements We require at least a Bachelor's degree in a related field or equivalent experience.
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.
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.
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 about our policy for using AI in our application process.
Seniority Level Mid-Senior level
Employment Type Full-time
Job Function Other
Industries Research Services
#J-18808-Ljbffr
Research Scientist, Interpretability
role at
Anthropic 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 When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. We’re looking for researchers and engineers to join our efforts.
People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Think of us as doing the "biology" or "neuroscience" of neural networks using microscopes we build, or treating neural networks as binary computer programs we are trying to reverse engineer.
For an overview of our work, see our research lead's introduction to Interpretability, the Hard Fork podcast episode, and our recent blog post with accompanying video. Some of our notable publications include "A Mathematical Framework for Transformer Circuits", "In-context Learning and Induction Heads", "Toy Models of Superposition", "Scaling Monosemanticity", and our Circuits’ Methods and Biology papers.
Responsibilities
Develop methods for understanding LLMs by reverse engineering algorithms learned in their weights
Design and run robust experiments, both quickly in toy scenarios and at scale in large models
Create and analyze new interpretability features and circuits to better understand how models work
Build infrastructure for running experiments and visualizing results
Work with colleagues to communicate results internally and publicly
You May Be a Good Fit If You
Have a strong track record of scientific research (in any field), and have done some work on Interpretability
Enjoy team science – working collaboratively to make big discoveries
Are comfortable with messy experimental science. We're inventing the field as we work, and the first textbook is years away
You view research and engineering as two sides of the same coin. Every team member writes code, designs and runs experiments, and interprets results
You can clearly articulate and discuss the motivations behind your work, and teach us about what you've learned. You like writing up and communicating your results, even when they're null
To learn more about the skills we look for and how to prepare for this role, see our blog post – "So You Want to Work in Mechanistic Interpretability?"
Familiarity with Python is required for this role.
Role Specific Location Policy This role is based in San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis.
Annual Salary $315,000—$560,000 USD
Education Requirements We require at least a Bachelor's degree in a related field or equivalent experience.
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.
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.
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 about our policy for using AI in our application process.
Seniority Level Mid-Senior level
Employment Type Full-time
Job Function Other
Industries Research Services
#J-18808-Ljbffr