Research Scientist, Agent Robustness
Scale AI · San Francisco, CA; New York, NY · San Francisco, CA
CHECKED 15H AGO
Infrastructureonsite
At a glance
Highlights
- Tackle agent robustness, control protocols and AI risk evaluations.
- Build harnesses testing agents pressured or tricked into harmful actions.
- Publish findings bridging AI research and global policymakers on AI risk.
What they offer
- Base salary
- Equity compensation
- Comprehensive health and dental benefits
Ideal candidate
Published ML researcher with 3+ years tackling complex problems who prototypes quickly and cares deeply about safe, trustworthy AI agents.
Requirements
- At least three years addressing sophisticated ML problems in research or product development
- Practical collaborative technical research experience building agent scaffolding and evaluation harnesses
- Experience with post-training and RL techniques such as RLHF, DPO, GRPO
- Track record of published ML research, particularly in generative AI
- Strong written and verbal communication skills for cross-functional work
- Commitment to safe, secure, and trustworthy AI deployments
- hiring process
- Research interviews assess practical ML prototyping and debugging, grasp of research concepts, and culture fit; no LeetCode-style questions.
Lab profile
About Scale AI
AI data foundry providing high-quality data for training, fine-tuning, and evaluating AI systems.
What they build
- Training, fine-tuning, and evaluation data for frontier models
- Multimodal and coding data for audio, image, video and world models
- Custom AI applications for enterprise and global public sector
Known for
- Leading data partner for frontier model developers
- Trusted across enterprise, defense and public sector
- Depth in multimodal, coding and physical AI
- End-to-end capability from strategy to delivery and evaluation
Key facts
- Founded in 2016
- Headquartered in San Francisco, California
- Private company backed by Accel, Founders Fund, Index Ventures, Nvidia and Meta