Machine Learning Fellow - Human Frontier Collective
Scale AI · United States · Remote (Growth only)
CHECKED 14H AGO
Infrastructureremotesenior
At a glance
Highlights
- Build AI safety and policy guardrails shaping how frontier systems behave.
- Design experiments and RL environments to evaluate frontier AI models.
- Co-author research papers with Scale's team to boost academic visibility.
What they offer
- Regular matching to high-impact AI projects with Scale AI and partners
- Opportunity to co-author technical reports and research papers with Scale's research team
- Flexible self-set schedule with no minimum commitment, typically 10-25 hours per week
- Access to expert network, newsletters, discussion channels, virtual sessions and IRL events
Ideal candidate
PhD-level researcher or seasoned ML practitioner who loves applied AI and collaboration. Detail-oriented innovator eager to shape human-centered frontier AI and publish impactful work.
Requirements
- PhD or postdoctoral research experience in Machine Learning, Computer Science or related field, or senior industry experience in ML
- Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow)
- Experience with AWS, Docker and LangChain is a plus
- Detail-oriented, innovative thinker with passion for applied AI research and commitment to collaboration
- Full-time work authorization in the US
- remote policy
- Fully remote
- visa sponsorship
- No visa sponsorship
- hiring process
- Rolling application review followed by interview on research experience and mission alignment, then invitation to join the Collective.
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