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About the Role
This role is within the Agent Data and Optimization team, which serves as the Applied AI organization's data and research environment engine. The team transforms technical expertise into training data, reinforcement learning (RL) environments, evaluations, and feedback loops to enhance Meta's models and products. The work directly improves Muse family of models and powers products like Muse Code and the Muse assistant. This role offers the opportunity to work directly on frontier AI models within a well-funded organization that combines the impact of a startup with the resources of a large company.
Responsibilities
- Identify capability gaps and formulate research questions that advance AI agents’ reasoning and problem-solving abilities.
- Develop research methods, benchmarks and experimental environments with reliable, reproducible measurements.
- Create and curate high-quality data, and build pipelines that support model training and evaluation.
- Analyze agent behavior and design feedback that rewards useful progress and tests generalization to new problems.
- Lead research from hypothesis through implementation and measured results, collaborating with Meta’s model development and research teams.
Requirements
- A PhD in Computer Science, AI, relevant technical field, or equivalent practical experience
- 3+ Years Experience leading major research initiatives or influencing technical strategy across teams
- Demonstrated ability to build reliable technical systems and evaluate their results
- A strong track record of first-author publication on AI-related topics with experience presenting the work
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Experience Level
- 3+ Years Experience leading major research initiatives or influencing technical strategy across teams
Education Level
- PhD in Computer Science, AI, relevant technical field, or equivalent practical experience
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Salary/Compensations
- $154,003/year to $217,000/year
Benefits
- bonus
- equity
- benefits
About the Company
- The Agent Data and Optimization team is part of the Applied AI organization.
- The team's research and agentic work directly improves Muse family of models and powers products such as Muse Code and the Muse assistant.
- This unique data and research infrastructure is a key differentiator for Meta, complementing our investments in compute and model architecture.
- We’re a significant, well-funded organization with the ethos of an AI startup: new, highly entrepreneurial, flexible, and already delivering measurable impact.
- Research and RL environments from our team went directly into the latest Muse release and helped the Muse family of models compete at the frontier.