Role overview

The Human Frontier Collective (HFC) is seeking a Machine Learning Fellow to join an exclusive network of top researchers and domain experts shaping the future of AI. Scale AI brings together over 90% doctorate holders across 70+ fields to develop reliable AI systems for critical decisions and to advance human-centered approaches to frontier AI development.

Key responsibilities

Participate in carefully selected AI and machine learning projects alongside Scale AI partners, which may include evaluating AI models, designing experiments, or building reinforcement learning environments.
Design, review, and optimize PyTorch models to help frontier AI systems understand real-world deep learning workflows and applications.
Evaluate complex machine learning code and AI-generated implementations for efficiency, correctness, and safety.
Contribute to building AI safety and policy guardrails for frontier AI systems.
Co-author technical reports and research papers with Scale’s research team to advance published work in the field.
Engage with an interdisciplinary network through newsletters, discussion channels, virtual sessions, and in-person events.

Requirements

Hold a PhD or postdoctoral research experience in Machine Learning, Computer Science, or a related field, or demonstrate senior-level industry experience in machine learning.
Possess strong proficiency in Python and modern machine learning frameworks such as PyTorch or TensorFlow.
Have experience with cloud infrastructure platforms like AWS and containerization tools such as Docker.
Demonstrate a detail-oriented and innovative approach to applied AI research with a genuine commitment to collaboration.
Maintain full-time work authorization in the United States; visa sponsorship is not available.

What makes this role worth considering

This is a fully remote, flexible engagement with no fixed end date and no minimum hours required—most fellows dedicate 10–25 hours per week on their own schedule. You’ll join an elite interdisciplinary community of leading researchers and thought leaders from top institutions while gaining access to exclusive networking opportunities, publishing collaborations, and high-impact AI projects that directly influence how frontier systems are built and governed.