AI Research Scientist

About the Role

The FAIR Security, Privacy, and Reliability team conducts fundamental research on AI agents and foundational models. The team focuses on discovering novel attacks, measuring privacy, and identifying non-intuitive breaks in robustness. Research findings are contributed to Meta's model Evaluation Reports and published in top research venues. The team also develops and implements novel post-training mitigations for these risks, with opportunities for direct research-to-production.

Key Responsibilities

• Conduct fundamental research to discover novel safety and security failures, 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 the 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.

Requirements & Tech Stack

• Research experience in at least one of the following 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)
• developing mitigations in any of the above areas
• Track record of publications in top-tier research venues.

Qualifications

• Compensation: $122,000/year to $181,000/year + bonus + equity + benefits
• Individual compensation is determined by skills, qualifications, experience, and location.
• Compensation details listed reflect base rate only and do not include bonus, equity, or sales incentives.
• Meta offers benefits.