Research Scientist, Safety Post Training
Scale AI · San Francisco, CA | New York City, NY · Research
About this role
Scale AI is hiring a mid-level Research Scientist in the machine learning function based in San Francisco, CA | New York City, NY. The posting calls out experience with LLMs, Reinforcement Learning, Machine Learning, Full Stack. Compensation is listed at $216,000–$270,000 per year.
- Role
- Research Scientist
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- San Francisco, CA | New York City, NY
- Department
- Research
More roles at Scale AI
Job description
from Scale AI careersAs the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities.
Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision.
As a Research Scientist working on Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might:
- Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties;
- Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations;