Bachelor's degree in Computer Science, Computer Engineering, or a related field (must be completed before joining)
PhD in Computer Science, Machine Learning, or equivalent experience
Research experience in safety, security, privacy, or robustness of AI models
Familiarity with adversarial machine learning and related vulnerabilities
Experience in developing mitigations for catastrophic risks in AI systems
Responsibilities
Conduct fundamental research to identify safety and security failures in AI agents
Develop benchmarks for Meta's foundational model evaluation suite
Design and implement post-training mitigations for various risks
Collaborate with cross-functional teams to translate research into production systems
Benefits
Opportunities for direct research-to-production impact
Access to cutting-edge research and development resources
Collaboration with top-tier professionals in the field
Recognition for contributions to high-impact research venues
Full Job Description
The FAIR Security, Privacy, and Reliability team breaks and fixes agents and the foundational models that power them. We conduct fundamental research to discover novel attacks, measure privacy, and find non-intuitive breaks in robustness. We frequently contribute those benchmarks to Meta's model Evaluation Reports and have published many of them in top research venues, earning top-1% recognition at ICLR and ICML. The team also lands novel post-training mitigations for these risks in both the open-source line of models and has multiple opportunities for direct research-to-production.
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
Minimum Qualifications • Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta • PhD in Computer Science, Machine Learning, or related field, or equivalent practical experience • 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); or developing mitigations in any of these areas
Preferred Qualifications • Track record of publications in top-tier research venues
