Machine Learning Research Scientist, Evaluations
Scale AI · San Francisco, CA; Seattle, WA; New York, NY · San Francisco, CA
CHECKED 15H AGO
Infrastructureonsite$166k–$207k
At a glance
Highlights
- Build benchmarks diagnosing failure modes in frontier LLMs and agents.
- Develop rigorous evaluations for text and multimodal frontier models.
- Partner with leading AI labs to shape next-generation generative models.
What they offer
- Equity compensation
- Comprehensive health, dental and vision coverage
- Retirement benefits
- Learning and development stipend
- Generous PTO
- Commuter stipend
Ideal candidate
PhD researcher passionate about understanding why frontier models fail and turning rigorous evaluation into better models. You love diagnosing behavior, collaborating with top labs, and publishing impactful work.
Requirements
- Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or related field
- Deep understanding of deep learning, reinforcement learning, and large-scale fine-tuning
- Experience with post-training techniques and LLM evaluation or benchmark development
- Excellent written and verbal communication skills
- Published research at major ML conferences and/or journals
- Previous experience in a customer facing role
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