Research Engineer, Privacy Evals - Meta Superintelligence Labs
Menlo Park, CAJob$154–217K/yrSeen 3 days agoSeen in employer's feed today
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Job overview
Meta is seeking Research Engineers to join the Data & Privacy Research team within Meta Superintelligence Labs. The team studies, evaluates and aligns Meta's frontier AI models with privacy expectations, measuring and mitigating risks from pre‑training data curation to post‑training alignment. The role involves developing evaluations, maintaining pipelines, and producing technical artifacts to inform launch decisions.
Skills & qualifications
Skills
Qualifications
Full job description
Summary:
Meta is seeking Research Engineers to join the Data & Privacy Research team within Meta Superintelligence Labs. This team studies, evaluates and aligns Meta's frontier AI model and systems, with a focus on memorization & privacy risks. We ensure that our frontier models and agents operate and behave within users' privacy and Meta's privacy expectations by rigorously measuring and mitigating across the entire frontier model development lifecycle - pre-training data curation to post-training alignment. As a Research Engineer on this team, you will work alongside AI researchers to develop new evaluations grounded in real-world threat models, maintain existing evaluations so they remain current and reliable, and produce written artifacts that Meta can trust during high-stakes launches. This is a highly technical role requiring the ability to deeply understand frontier LLM behavior, hypothesize and design true and grounded risk vectors and turn them into automated evaluations with high scalability and reliability. The evaluations you build will directly inform risk assessments and launch decisions within Meta Superintelligence Labs, making engineering reliability, rigor, and scalability paramount. You will succeed by delivering iteratively while re-prioritizing work based on evolving research needs and launch timelines as we advance the technical research frontier. The evaluations you produce will significantly influence pre-training data mixes, model behavior during post-training and will be read and acted upon by Meta's leadership during model launches and policy reviews.
Required Skills:
Research Engineer, Privacy Evals - Meta Superintelligence Labs Responsibilities:
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Build and continuously refine evaluations for multimodal and agentic frontier AI models across pretraining and post-training
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Build robust, reusable evaluation pipelines that scale across multiple model lines and product areas
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Produce auditable technical artifacts, including evaluation reports and model cards, at high reliability and speed
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Scope and deliver end-to-end evaluations under ambiguous and rapidly shifting requirements, re-prioritizing as the threat landscape and Meta’s frontier models evolve
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Work across research, engineering, policy, and legal teams to align evaluation priorities with launch timelines
Minimum Qualifications:
Minimum Qualifications:
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Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
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1+ years of experience in ML engineering, LLM research, or a related technical role
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Background in one or multiple of privacy-preserving LLM development, memorization, pretraining data curation and post-training alignment
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Proficiency in Python and experience with machine learning frameworks
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Experience scoping, designing, and delivering medium-to-large technical projects with minimal direction, defining milestones and coordinating dependencies
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Proven experience in software engineering practices, including version control, testing, and code review practices
Preferred Qualifications:
Preferred Qualifications:
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Experience working with large-scale distributed systems and data pipelines
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Experience in implementing or developing benchmarks for large language models and multimodal models (e.g., vision-language, audio, video, browser agents)
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Experience in red-teaming AI systems, adversarial machine learning, or abuse prevention systems
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Publications at peer-reviewed venues (NeurIPS, ICML, ICLR, ACL, EMNLP, or similar) related to language model evaluation, AI safety, or deep learning
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PhD or Master's degree in Computer Science or relevant technical field, or equivalent practical experience with a focus on privacy and/or safety domains
Public Compensation:
$154,003/year to $217,000/year + bonus + equity + benefits
Industry: Internet
Equal Opportunity:
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 [email protected].
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