Data Scientist, Evaluations - Meta Superintelligence Labs
Meta - Menlo Park, CA; New York, NY
Posted Jun 4, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
-
- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified checked Jun 7, 2026
- Salary
- $177K-$247K From the posting source checked Jun 20, 2026
- 401(k) match
- Reported from DOL Form 5500 industry filing (not employer-specific)
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Market context
- U.S. role benchmark (BLS OEWS)
- $111,944 U.S. median for this role
- Projected growth (BLS Employment Projections)
- +13.7% - Much faster than average
89% above the BLS role benchmark for data and ml aggregate.
Matched to SOC 15-1252 - Data and ML aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Role
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Company
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Data Scientist, Evaluations - Meta Superintelligence Labs Menlo Park, CA; New York, NY Meta is seeking a Data Scientist to join the Evaluations team within Meta Superintelligence Labs (MSL). Evaluations are the core of AI progress at MSL, determining what capabilities get built, which features get prioritized, and how fast our models improve. As a Data Scientist on this team, you will be responsible for the scientific rigor behind our frontier AI benchmarks. You will work in tandem with world-class Research Scientists and Engineers to design, validate, and analyze novel evaluations that shape the future of AI capability measurement. This role is for a technical Data Science expert who can bridge the gap between abstract model capabilities and rigorous, unbiased measurement. You will lead the charge on sampling strategies for various AI tasks, critically examine benchmark quality and validity, and perform deep-dive analysis on current frontier models' failures and limitations. You will have the opportunity to conduct novel research, think creatively about measurement in uncharted territories, and contribute to the global AI community. Responsibilities: - 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
Read the full description at www.metacareers.com. FewerJobs shows a preview and links to the original posting.
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