AI Safety Residency - SLPreP
Scale AI · Canada; United Kingdom; United States · Remote (Growth only)
Infrastructureremote
At a glance
Highlights
- Own empirical AI safety projects probing where frontier models fail under pressure.
- Build evaluation harnesses for control, monitoring and multi-agent safety.
- Publish safety research aimed at top venues like NeurIPS, ICML and ICLR.
What they offer
- Own a substantial part of a safety research project with weekly mentor guidance
- Produce reproducible research with papers submitted to NeurIPS, ICML, ICLR
Ideal candidate
PhD-track researcher driven by safe advanced AI, who thrives owning open-ended empirical questions end-to-end and turning messy agent behaviors into rigorous, reproducible evaluations.
Requirements
- Pursuing or completed PhD in CS, ML, statistics, mathematics or related field
- Motivated by safe and responsible development of advanced AI systems
- Interested in technical safety research including alignment, control and monitoring
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
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