AI Safety & Security Research Scientist Foundational Models

Meta; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Meta's FAIR Security, Privacy, and Reliability team is seeking researchers to break and fix agents and foundational models, driving safer and more reliable AI systems. You will develop benchmarks and contribute to Evaluation Reports, and design post-training mitigations for risks in foundation models.

Collaborate with cross-functional teams to translate research into production systems and publish findings in top venues, advancing measurement of memorization, privacy, and reliability in AI

Qualifications

• PhD preferred or equivalent practical experience.
• Track record of publications in top-tier venues in safety, security, privacy, or robustness of AI models.

Responsibilities

• Conduct fundamental research to discover safety and security failures and robust evaluation methods for AI agents and foundation models.
• Develop benchmarks and contribute to Meta’s evaluation suite and reports.
• Design and implement post-training mitigations for safety, security, privacy, and reliability risks in foundation models.
• Collaborate with cross-functional teams to translate research into production systems.

Skills

Safety research

Adversarial ML

Robustness

Research publications

Education

Bachelor's degree in CS/EE or equivalent

PhD in CS/ML or related field

Job description

Meta's FAIR Security, Privacy, and Reliability team is seeking researchers to break and fix agents and foundational models, driving safer and more reliable AI systems. You will develop benchmarks and contribute to Evaluation Reports, and design post-training mitigations for risks in foundation models.

Collaborate with cross-functional teams to translate research into production systems and publish findings in top venues, advancing measurement of memorization, privacy, and reliability in AI