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 As a Technical Program Manager for model evaluations, you will own end-to-end coordination of our evaluation ecosystem—from shaping eval strategy during early model development through launch execution. You will be the critical bridge between Research, Product, Marketing, and Engineering teams, sitting at the intersection of frontier AI research and product launches.
Launch Coordination
Standardize how evaluation results are generated, documented, compared across model versions, and communicated to stakeholders.
Own end-to-end eval readiness for model launches—tracking which evals are ready, which need scores on past models, and which meet the bar for marketing materials.
Establish and enforce clear criteria for eval inclusion: scores on historical models, state-of-the-art performance, and competitor comparisons.
Coordinate between research teams, marketing, and product to consolidate eval status into a single source of truth.
Maintain a high bar: ensure reported statistics reflect model capabilities in an honest, accurate, and transparent way.
Ecosystem Development
Get involved early in model development cycles, helping shape eval plans for RL environments.
Partner with research and infrastructure teams to improve underlying evals infrastructure—eval-syncer reliability, results storage and querying, automation capabilities.
Drive prioritization of eval tooling enhancements based on researcher needs.
Identify patterns across launches and drive systemic fixes rather than point solutions.
Work with PMs and researchers to improve and implement high-priority eval launches.
Maintain and prioritize the eval roadmap—working with cross-functional teams to identify which new evals are needed for upcoming launches and product requirements.
Implement an operating model that reflects an evals environment with increasing complexity.
Process & Systems
Build lightweight but rigorous tracking systems—moving key information into structured formats that enable better decision-making.
Create eval dashboards that provide real-time visibility into training progress on hero evals, enabling earlier intervention when scores look concerning.
Document eval processes, requirements, and lessons learned to build institutional knowledge.
Coordinate compute allocation for large-scale evals with infrastructure teams.
You May Be a Good Fit If You
Have 5+ years of technical program management experience with a track record of bringing order to chaotic, high‑stakes coordination problems.
Possess scientific depth and a very high quality bar for data.
Have experience with ML/AI evaluation methodologies, benchmarking, or research quality assurance.
Have a background in research operations, scientific publishing, or data quality management.
Have previous experience as data analyst, data scientist, or software engineer.
Can build trust with research teams by understanding their work deeply enough to add value beyond coordination.
Are skilled at cross‑functional coordination involving research, product, marketing, and engineering—navigating competing priorities and driving alignment.
Have working familiarity with data analysis tools (SQL, Python, or similar) for querying eval results and building dashboards.
Have familiarity with LLM capabilities and limitations and experience working with AI research teams.
Excel at written and verbal communication, translating technical nuance for marketing stakeholders while maintaining precision.
Thrive in unstructured environments with a bias toward action and a knack for creating clarity in ambiguous situations.
Have extremely high ownership and attention to detail.
Deadline to apply: None—applications will be received on a rolling basis.
Compensation: $290,000 - $365,000 USD (base); total compensation package includes equity, benefits, and may include incentive compensation.
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. Some roles may require more time in our offices.
Visa sponsorship:
We sponsor visas. We retain an immigration lawyer to help with this, but we cannot always sponsor every role.
Application encouragement:
We encourage you to apply even if you do not believe you meet every qualification. Underrepresented groups may experience imposter syndrome; we urge you not to exclude yourself prematurely.
How we’re different We believe the highest-impact AI research comes from large‑scale, collaborative efforts. We value impact—advancing long‑term goals of steerable, trustworthy AI—over small‑scale puzzles. Communication and collaboration are highly valued.
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 to collaborate with colleagues.
Equal Employment Opportunity 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.
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About the Role As a Technical Program Manager for model evaluations, you will own end-to-end coordination of our evaluation ecosystem—from shaping eval strategy during early model development through launch execution. You will be the critical bridge between Research, Product, Marketing, and Engineering teams, sitting at the intersection of frontier AI research and product launches.
Launch Coordination
Standardize how evaluation results are generated, documented, compared across model versions, and communicated to stakeholders.
Own end-to-end eval readiness for model launches—tracking which evals are ready, which need scores on past models, and which meet the bar for marketing materials.
Establish and enforce clear criteria for eval inclusion: scores on historical models, state-of-the-art performance, and competitor comparisons.
Coordinate between research teams, marketing, and product to consolidate eval status into a single source of truth.
Maintain a high bar: ensure reported statistics reflect model capabilities in an honest, accurate, and transparent way.
Ecosystem Development
Get involved early in model development cycles, helping shape eval plans for RL environments.
Partner with research and infrastructure teams to improve underlying evals infrastructure—eval-syncer reliability, results storage and querying, automation capabilities.
Drive prioritization of eval tooling enhancements based on researcher needs.
Identify patterns across launches and drive systemic fixes rather than point solutions.
Work with PMs and researchers to improve and implement high-priority eval launches.
Maintain and prioritize the eval roadmap—working with cross-functional teams to identify which new evals are needed for upcoming launches and product requirements.
Implement an operating model that reflects an evals environment with increasing complexity.
Process & Systems
Build lightweight but rigorous tracking systems—moving key information into structured formats that enable better decision-making.
Create eval dashboards that provide real-time visibility into training progress on hero evals, enabling earlier intervention when scores look concerning.
Document eval processes, requirements, and lessons learned to build institutional knowledge.
Coordinate compute allocation for large-scale evals with infrastructure teams.
You May Be a Good Fit If You
Have 5+ years of technical program management experience with a track record of bringing order to chaotic, high‑stakes coordination problems.
Possess scientific depth and a very high quality bar for data.
Have experience with ML/AI evaluation methodologies, benchmarking, or research quality assurance.
Have a background in research operations, scientific publishing, or data quality management.
Have previous experience as data analyst, data scientist, or software engineer.
Can build trust with research teams by understanding their work deeply enough to add value beyond coordination.
Are skilled at cross‑functional coordination involving research, product, marketing, and engineering—navigating competing priorities and driving alignment.
Have working familiarity with data analysis tools (SQL, Python, or similar) for querying eval results and building dashboards.
Have familiarity with LLM capabilities and limitations and experience working with AI research teams.
Excel at written and verbal communication, translating technical nuance for marketing stakeholders while maintaining precision.
Thrive in unstructured environments with a bias toward action and a knack for creating clarity in ambiguous situations.
Have extremely high ownership and attention to detail.
Deadline to apply: None—applications will be received on a rolling basis.
Compensation: $290,000 - $365,000 USD (base); total compensation package includes equity, benefits, and may include incentive compensation.
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. Some roles may require more time in our offices.
Visa sponsorship:
We sponsor visas. We retain an immigration lawyer to help with this, but we cannot always sponsor every role.
Application encouragement:
We encourage you to apply even if you do not believe you meet every qualification. Underrepresented groups may experience imposter syndrome; we urge you not to exclude yourself prematurely.
How we’re different We believe the highest-impact AI research comes from large‑scale, collaborative efforts. We value impact—advancing long‑term goals of steerable, trustworthy AI—over small‑scale puzzles. Communication and collaboration are highly valued.
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 to collaborate with colleagues.
Equal Employment Opportunity 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.
#J-18808-Ljbffr