AI Research Scientist, FAIR Security, Privacy, and Reliability

Meta•Seattle, WA
•$122,000 - $181,000

About The Position

The FAIR Security, Privacy, and Reliability team conducts fundamental research to discover novel attacks, measure privacy, and identify non-intuitive robustness failures in AI agents and foundational models. The team contributes benchmarks to Meta's model Evaluation Reports and publishes research in top venues, with top-1% recognition at ICLR and ICML. It also develops post-training mitigations for risks in Meta's open-source model line, with opportunities to take research directly into production.

Requirements

  • Currently hold or be pursuing a Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience; the degree must be completed before joining Meta.
  • PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
  • Research experience in at least one of these areas: safety, security, privacy, or robustness of AI models; adversarial machine learning; indirect prompt injections or jailbreaks; contextual integrity or memorization; reward hacking or other agent reliability failures; testing or mitigating foundation models for catastrophic risk (CBRNE, cyber, loss of control); or developing mitigations in any of these areas.

Nice To Haves

  • Track record of publications in top-tier research venues.

Responsibilities

  • Conduct fundamental research to discover novel safety and security failures and develop robust approaches to measuring memorization risk or reliability failures in AI agents and foundational models.
  • Develop and contribute benchmarks to Meta's foundational model evaluation suite and/or Evaluation Reports.
  • Design and implement novel post-training mitigations for safety, security, privacy, and reliability risks in foundation models.
  • Collaborate with cross-functional teams to translate research into production systems.
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