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As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans.
Job Responsibility:
Research the science of AI agent capabilities with a focus on safety, risk factors, and benchmarking methodologies
Design and build harnesses to test AI agents’ tendency to take harmful actions
Design and build exploits and mitigations for new failure modes
Characterize and design mitigations for potential failure modes of systems involving multiple interacting AI agents
Requirements:
Commitment to mission of promoting safe, secure, and trustworthy AI deployments
Practical experience conducting technical research collaboratively
Experience building and leveraging agent scaffolding, designing evaluation harnesses, and quickly turning new ideas into working prototypes
Experience with post-training and RL techniques such as RLHF, DPO, GRPO
A track record of published research in machine learning, particularly in generative AI
At least three years of experience addressing sophisticated ML problems
Strong written and verbal communication skills
Nice to have:
Hands-on experience with agent evaluation frameworks such as SWE-bench, WebArena, OSWorld, Inspect
Experience with red-teaming, prompt injection, or adversarial testing of AI systems