Anthropic
Research Engineer, Model Evaluations
Anthropic, San Francisco, California, United States, 94199
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 Research Engineer on the Model Evaluations team, you'll lead the design and implementation of Anthropic's evaluation platform—a critical system that shapes how we understand, measure, and improve our models' capabilities and safety. You'll work at the intersection of research and engineering to develop and implement model evaluations that give us insight into emerging capabilities and build robust evaluation infrastructure that directly influences our training decisions and model development roadmap.
Your work will be essential to Anthropic's mission of building safe, beneficial AI systems. You'll collaborate closely with training teams, alignment researchers, and safety teams to ensure our models meet the highest standards before deployment. This is a technical leadership role where you'll drive both the strategic vision and hands‑on implementation of our evaluation systems.
Responsibilities
Design novel evaluation methodologies to assess model capabilities across diverse domains including reasoning, safety, helpfulness, and harmlessness
Lead the design and architecture of Anthropic's evaluation platform, ensuring it scales with our rapidly evolving model capabilities and research needs
Implement and maintain high‑throughput evaluation pipelines that run during production training, providing real‑time insights to guide training decisions
Analyze evaluation results to identify patterns, failure modes, and opportunities for model improvement, translating complex findings into actionable insights
Partner with research teams to develop domain‑specific evaluations that probe for emerging capabilities and potential risks
Build infrastructure to enable rapid iteration on evaluation design, supporting both automated and human‑in‑the‑loop assessment approaches
Establish best practices and standards for evaluation development across the organization
Mentor team members and contribute to the growth of evaluation expertise at Anthropic
Coordinate evaluation efforts during critical training runs, ensuring comprehensive coverage and timely results
Contribute to research publications and external communications about evaluation methodologies and findings
You may be a good fit if you
Have experience designing and implementing evaluation systems for machine learning models, particularly large language models
Have demonstrated technical leadership experience, either formally or through leading complex technical projects
Are skilled at both systems engineering and experimental design, comfortable building infrastructure while maintaining scientific rigor
Have strong programming skills in Python and experience with distributed computing frameworks
Can translate between research needs and engineering constraints, finding pragmatic solutions to complex problems
Are results‑oriented and thrive in fast‑paced environments where priorities can shift based on research findings
Enjoy collaborative work and can effectively communicate technical concepts to diverse stakeholders
Care deeply about AI safety and the societal impacts of the systems we build
Have experience with statistical analysis and can draw meaningful conclusions from large‑scale experimental data
Strong candidates may also have
Experience with evaluation during model training, particularly in production environments
Familiarity with safety evaluation frameworks and red teaming methodologies
Background in psychometrics, experimental psychology, or other fields focused on measurement and assessment
Experience with reinforcement learning evaluation or multi‑agent systems
Contributions to open‑source evaluation benchmarks or frameworks
Knowledge of prompt engineering and its role in evaluation design
Experience managing evaluation infrastructure at scale (thousands of experiments)
Published research in machine learning evaluation, benchmarking, or related areas
Representative projects
Designing comprehensive evaluation suites that assess models across hundreds of capability dimensions
Building real‑time evaluation dashboards that surface critical insights during multi‑week training runs
Developing novel evaluation approaches for emerging capabilities like multi‑step reasoning or tool use
Creating automated systems to detect regression in model performance or safety properties
Implementing efficient evaluation sampling strategies that balance coverage with computational constraints
Collaborating with external partners to develop industry‑standard evaluation benchmarks
Building infrastructure to support human evaluation at scale, including quality control and aggregation systems
The expected base compensation for this position is below. Our total compensation package for full‑time employees includes equity, benefits, and may include incentive compensation.
$300,000 - $405,000 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 do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. 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.
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.
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.
As set forth in Anthropic’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows:
A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service‑connected disability.
A "recently separated veteran" means any veteran during the three‑year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.
An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.
An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.
Voluntary Self‑Identification of Disability Form CC-305
Page 1 of 1
OMB Control Number 1250-0005
Expires 04/30/2026
Why are you being asked to complete this form? We are a federal contractor or subcontractor. The law requires us to provide equal employment opportunity to qualified people with disabilities. We have a goal of having at least 7% of our workers as people with disabilities. The law says we must measure our progress towards this goal. To do this, we must ask applicants and employees if they have a disability or have ever had one. People can become disabled, so we need to ask this question at least every five years.
Completing this form is voluntary, and we hope that you will choose to do so. Your answer is confidential. No one who makes hiring decisions will see it. Your decision to complete the form and your answer will not harm you in any way. If you want to learn more about the law or this form, visit the U.S. Department of Labor’s Office of Federal Contract Compliance Programs (OFCCP) website at www.dol.gov/ofccp.
How do you know if you have a disability? A disability is a condition that substantially limits one or more of your “major life activities.” If you have or have ever had such a condition, you are a person with a disability. Disabilities include, but are not limited to:
Alcohol or other substance use disorder (not currently using drugs illegally)
Autoimmune disorder, for example, lupus, fibromyalgia, rheumatoid arthritis, HIV/AIDS
Blind or low vision
Cancer (past or present)
Cardiovascular or heart disease
Celiac disease
Cerebral palsy
Deaf or serious difficulty hearing
Diabetes
Disfigurement, for example, disfigurement caused by burns, wounds, accidents, or congenital disorders
Epilepsy or other seizure disorder
Gastrointestinal disorders, for example, Crohn's Disease, irritable bowel syndrome
Intellectual or developmental disability
Mental health conditions, for example, depression, bipolar disorder, anxiety disorder, schizophrenia, PTSD
Missing limbs or partially missing limbs
Mobility impairment, benefiting from the use of a wheelchair, scooter, walker, leg brace(s) and/or other supports
Nervous system condition, for example, migraine headaches, Parkinson’s disease, multiple sclerosis (MS)
Neurodivergence, for example, attention‑deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities
Partial or complete paralysis (any cause)
Pulmonary or respiratory conditions, for example, tuberculosis, asthma, emphysema
Short stature (dwarfism)
Traumatic brain injury
Disability Status Select...
PUBLIC BURDEN STATEMENT: According to the Paperwork Reduction Act of 1995 no persons are required to respond to a collection of information unless such collection displays a valid OMB control number. This survey should take about 5 minutes to complete.
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About the role As a Research Engineer on the Model Evaluations team, you'll lead the design and implementation of Anthropic's evaluation platform—a critical system that shapes how we understand, measure, and improve our models' capabilities and safety. You'll work at the intersection of research and engineering to develop and implement model evaluations that give us insight into emerging capabilities and build robust evaluation infrastructure that directly influences our training decisions and model development roadmap.
Your work will be essential to Anthropic's mission of building safe, beneficial AI systems. You'll collaborate closely with training teams, alignment researchers, and safety teams to ensure our models meet the highest standards before deployment. This is a technical leadership role where you'll drive both the strategic vision and hands‑on implementation of our evaluation systems.
Responsibilities
Design novel evaluation methodologies to assess model capabilities across diverse domains including reasoning, safety, helpfulness, and harmlessness
Lead the design and architecture of Anthropic's evaluation platform, ensuring it scales with our rapidly evolving model capabilities and research needs
Implement and maintain high‑throughput evaluation pipelines that run during production training, providing real‑time insights to guide training decisions
Analyze evaluation results to identify patterns, failure modes, and opportunities for model improvement, translating complex findings into actionable insights
Partner with research teams to develop domain‑specific evaluations that probe for emerging capabilities and potential risks
Build infrastructure to enable rapid iteration on evaluation design, supporting both automated and human‑in‑the‑loop assessment approaches
Establish best practices and standards for evaluation development across the organization
Mentor team members and contribute to the growth of evaluation expertise at Anthropic
Coordinate evaluation efforts during critical training runs, ensuring comprehensive coverage and timely results
Contribute to research publications and external communications about evaluation methodologies and findings
You may be a good fit if you
Have experience designing and implementing evaluation systems for machine learning models, particularly large language models
Have demonstrated technical leadership experience, either formally or through leading complex technical projects
Are skilled at both systems engineering and experimental design, comfortable building infrastructure while maintaining scientific rigor
Have strong programming skills in Python and experience with distributed computing frameworks
Can translate between research needs and engineering constraints, finding pragmatic solutions to complex problems
Are results‑oriented and thrive in fast‑paced environments where priorities can shift based on research findings
Enjoy collaborative work and can effectively communicate technical concepts to diverse stakeholders
Care deeply about AI safety and the societal impacts of the systems we build
Have experience with statistical analysis and can draw meaningful conclusions from large‑scale experimental data
Strong candidates may also have
Experience with evaluation during model training, particularly in production environments
Familiarity with safety evaluation frameworks and red teaming methodologies
Background in psychometrics, experimental psychology, or other fields focused on measurement and assessment
Experience with reinforcement learning evaluation or multi‑agent systems
Contributions to open‑source evaluation benchmarks or frameworks
Knowledge of prompt engineering and its role in evaluation design
Experience managing evaluation infrastructure at scale (thousands of experiments)
Published research in machine learning evaluation, benchmarking, or related areas
Representative projects
Designing comprehensive evaluation suites that assess models across hundreds of capability dimensions
Building real‑time evaluation dashboards that surface critical insights during multi‑week training runs
Developing novel evaluation approaches for emerging capabilities like multi‑step reasoning or tool use
Creating automated systems to detect regression in model performance or safety properties
Implementing efficient evaluation sampling strategies that balance coverage with computational constraints
Collaborating with external partners to develop industry‑standard evaluation benchmarks
Building infrastructure to support human evaluation at scale, including quality control and aggregation systems
The expected base compensation for this position is below. Our total compensation package for full‑time employees includes equity, benefits, and may include incentive compensation.
$300,000 - $405,000 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 do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. 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.
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.
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.
As set forth in Anthropic’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows:
A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service‑connected disability.
A "recently separated veteran" means any veteran during the three‑year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.
An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.
An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.
Voluntary Self‑Identification of Disability Form CC-305
Page 1 of 1
OMB Control Number 1250-0005
Expires 04/30/2026
Why are you being asked to complete this form? We are a federal contractor or subcontractor. The law requires us to provide equal employment opportunity to qualified people with disabilities. We have a goal of having at least 7% of our workers as people with disabilities. The law says we must measure our progress towards this goal. To do this, we must ask applicants and employees if they have a disability or have ever had one. People can become disabled, so we need to ask this question at least every five years.
Completing this form is voluntary, and we hope that you will choose to do so. Your answer is confidential. No one who makes hiring decisions will see it. Your decision to complete the form and your answer will not harm you in any way. If you want to learn more about the law or this form, visit the U.S. Department of Labor’s Office of Federal Contract Compliance Programs (OFCCP) website at www.dol.gov/ofccp.
How do you know if you have a disability? A disability is a condition that substantially limits one or more of your “major life activities.” If you have or have ever had such a condition, you are a person with a disability. Disabilities include, but are not limited to:
Alcohol or other substance use disorder (not currently using drugs illegally)
Autoimmune disorder, for example, lupus, fibromyalgia, rheumatoid arthritis, HIV/AIDS
Blind or low vision
Cancer (past or present)
Cardiovascular or heart disease
Celiac disease
Cerebral palsy
Deaf or serious difficulty hearing
Diabetes
Disfigurement, for example, disfigurement caused by burns, wounds, accidents, or congenital disorders
Epilepsy or other seizure disorder
Gastrointestinal disorders, for example, Crohn's Disease, irritable bowel syndrome
Intellectual or developmental disability
Mental health conditions, for example, depression, bipolar disorder, anxiety disorder, schizophrenia, PTSD
Missing limbs or partially missing limbs
Mobility impairment, benefiting from the use of a wheelchair, scooter, walker, leg brace(s) and/or other supports
Nervous system condition, for example, migraine headaches, Parkinson’s disease, multiple sclerosis (MS)
Neurodivergence, for example, attention‑deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities
Partial or complete paralysis (any cause)
Pulmonary or respiratory conditions, for example, tuberculosis, asthma, emphysema
Short stature (dwarfism)
Traumatic brain injury
Disability Status Select...
PUBLIC BURDEN STATEMENT: According to the Paperwork Reduction Act of 1995 no persons are required to respond to a collection of information unless such collection displays a valid OMB control number. This survey should take about 5 minutes to complete.
#J-18808-Ljbffr