Role overview
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$177,000/year to $247,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
What you'll work on
- Scientific Design & Validity: Lead the design of evaluation stimuli and benchmarks, ensuring they have minimal bias and high construct validity for frontier LLM capabilities
- Experimental Methodology: Design and execute effective sampling strategies and experimental frameworks to measure model performance and errors accurately
- Deep-Dive Analysis: Perform rigorous data and model error analyses to provide deep insights into model behavior, quality gaps, and failure modes
- Collaborative Research: Partner closely with Research Scientists and Engineers to translate organizational priorities into measurable, scientifically sound benchmarks
- External Impact: Drive the publication of novel evaluation research and the open-sourcing of benchmarks to influence the broader AI research community
- Strategic Influence: Use data-driven insights to influence research directions and major model development lines within MSL
What we're looking for
- Advanced Quantitative Background: Master’s or Ph.D. in a quantitative or experimentation-heavy field (e.g., Statistics, Psychology, Economics, Quantitative Social Sciences, or a related technical field)
- Publication Record: Publications at top-tier peer-reviewed venues (e.g., NeurIPS, ICML, ICLR, ACL, or field-specific journals) related to measurement, evaluation, or experimental design
- Evaluation Expertise: Recognized expertise in language model evaluation, psychometrics, or the science of benchmarking
- Open Source & Community: A track record of open-source contributions to evaluation tools, datasets, or benchmarks
- Domain Knowledge: Familiarity with language model post-training, RLHF, or the nuances of LLM failure modes
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies