Anthropic
Research Engineer / Scientist, Tool Use
Anthropic, San Francisco, California, United States, 94199
About Anthropic
Apply promptly! A high volume of applicants is expected for the role as detailed below, do not wait to send your CV. 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 team The Tool Use team within Research is responsible for making Claude the world's most capable, reliable, safe, and efficient model for tool use and agentic applications. The team focuses on the foundational layer - solving core problems such as tool call accuracy, long horizon & complex tool use workflow, large scale & dynamic tools, tool hallucination, tool use safety (e.g. prompt injection robustness), and tool use efficiency. These are foundations to the majority of Anthropic’s customers as well as internal teams building specific agentic capabilities such as coding (including Claude Code), search & deep research, memory, and multi-agents.
About the role We're looking for Research Engineers/Scientists to help us advance the frontier of tool use research. Today's AI agents handle impressive workflows. With tool use adoption accelerating rapidly across our platform, the next generation requires even more breakthrough research: for example, enabling models to reliably orchestrate vast tool ecosystems, maintain safety in autonomous operations, and scale to handle the increasing complexity of real-world tasks.
You'll collaborate with a diverse group of researchers and engineers to advance Claude's tool use capabilities and safety. You'll own the full research lifecycle—from identifying fundamental limitations to implementing solutions that ship in production models. We value diverse perspectives and exceptional depth in specific areas—whether that's groundbreaking RL research, exceptional engineering, or novel approaches from other quantitative fields.
Note: For this role, we conduct all interviews in Python.
Responsibilities
Define and pursue research agendas that push the boundaries of what's possible
Design and implement novel reinforcement learning environments and methodologies that push the state of the art of tool use
Build rigorous, realistic evaluations that capture the complexity of real-world tool use
Ship research advances that directly impact millions of users
Collaborate with other frontier research and product teams to drive fundamental breakthroughs in capabilities and safety, and work with teams to ship these into production
Design, implement, and debug code across our research and production ML stacks
Contribute to our collaborative research culture through pair programming, technical discussions, and team problem-solving
You may be a good fit if you
Are driven by real-world impact and excited to see research ship in production
Have strong machine learning research/applied-research experience, or a strong quantitative background such as physics, mathematics, or quant research
Write clean, reliable code and have solid software engineering skills
Communicate complex ideas clearly to diverse audiences
Are passionate about building AI systems that are both powerful and safe
Are hungry to learn and grow, regardless of years of experience
Strong candidates may also have
Experience with reinforcement learning techniques and environments
Experience with language model training, fine-tuning or evaluation
Experience building AI agents or autonomous systems
Published influential work in relevant ML areas
Deep expertise in a specific area (e.g., exceptional RL research, systems engineering, or mathematical foundations) even if still developing in other areas
Experience shipping features or working closely with product teams
Enthusiasm for pair programming and collaborative research
The salary range for this position is $315,000 - $425,000 USD.
Logistics 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 sponsor visas. If we make you an offer, we will make reasonable efforts to obtain 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 qualification as listed. We think AI systems like the ones we're building have enormous social and ethical implications, 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. 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 highly collaborative, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. 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.
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.
Interested in building your career at Anthropic? Get future opportunities sent straight to your email.
Voluntary Self-Identification For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file. We do not discriminate on the basis of protected status.
Voluntary Self-Identification of Disability We are a federal contractor or subcontractor. The law requires us to provide equal employment opportunity to qualified people with disabilities. The goal is to measure progress toward this goal. Completing this form is voluntary and confidential. No one who makes hiring decisions will see it. If you want to learn more about the law or this form, visit the U.S. Department of Labor's OFCCP website.
#J-18808-Ljbffr
Apply promptly! A high volume of applicants is expected for the role as detailed below, do not wait to send your CV. 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 team The Tool Use team within Research is responsible for making Claude the world's most capable, reliable, safe, and efficient model for tool use and agentic applications. The team focuses on the foundational layer - solving core problems such as tool call accuracy, long horizon & complex tool use workflow, large scale & dynamic tools, tool hallucination, tool use safety (e.g. prompt injection robustness), and tool use efficiency. These are foundations to the majority of Anthropic’s customers as well as internal teams building specific agentic capabilities such as coding (including Claude Code), search & deep research, memory, and multi-agents.
About the role We're looking for Research Engineers/Scientists to help us advance the frontier of tool use research. Today's AI agents handle impressive workflows. With tool use adoption accelerating rapidly across our platform, the next generation requires even more breakthrough research: for example, enabling models to reliably orchestrate vast tool ecosystems, maintain safety in autonomous operations, and scale to handle the increasing complexity of real-world tasks.
You'll collaborate with a diverse group of researchers and engineers to advance Claude's tool use capabilities and safety. You'll own the full research lifecycle—from identifying fundamental limitations to implementing solutions that ship in production models. We value diverse perspectives and exceptional depth in specific areas—whether that's groundbreaking RL research, exceptional engineering, or novel approaches from other quantitative fields.
Note: For this role, we conduct all interviews in Python.
Responsibilities
Define and pursue research agendas that push the boundaries of what's possible
Design and implement novel reinforcement learning environments and methodologies that push the state of the art of tool use
Build rigorous, realistic evaluations that capture the complexity of real-world tool use
Ship research advances that directly impact millions of users
Collaborate with other frontier research and product teams to drive fundamental breakthroughs in capabilities and safety, and work with teams to ship these into production
Design, implement, and debug code across our research and production ML stacks
Contribute to our collaborative research culture through pair programming, technical discussions, and team problem-solving
You may be a good fit if you
Are driven by real-world impact and excited to see research ship in production
Have strong machine learning research/applied-research experience, or a strong quantitative background such as physics, mathematics, or quant research
Write clean, reliable code and have solid software engineering skills
Communicate complex ideas clearly to diverse audiences
Are passionate about building AI systems that are both powerful and safe
Are hungry to learn and grow, regardless of years of experience
Strong candidates may also have
Experience with reinforcement learning techniques and environments
Experience with language model training, fine-tuning or evaluation
Experience building AI agents or autonomous systems
Published influential work in relevant ML areas
Deep expertise in a specific area (e.g., exceptional RL research, systems engineering, or mathematical foundations) even if still developing in other areas
Experience shipping features or working closely with product teams
Enthusiasm for pair programming and collaborative research
The salary range for this position is $315,000 - $425,000 USD.
Logistics 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 sponsor visas. If we make you an offer, we will make reasonable efforts to obtain 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 qualification as listed. We think AI systems like the ones we're building have enormous social and ethical implications, 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. 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 highly collaborative, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. 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.
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.
Interested in building your career at Anthropic? Get future opportunities sent straight to your email.
Voluntary Self-Identification For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file. We do not discriminate on the basis of protected status.
Voluntary Self-Identification of Disability We are a federal contractor or subcontractor. The law requires us to provide equal employment opportunity to qualified people with disabilities. The goal is to measure progress toward this goal. Completing this form is voluntary and confidential. No one who makes hiring decisions will see it. If you want to learn more about the law or this form, visit the U.S. Department of Labor's OFCCP website.
#J-18808-Ljbffr