Role overview

The Human Frontier Collective (HFC) is seeking a Machine Learning Fellow to join an exclusive network of top researchers and domain experts dedicated to shaping the future of frontier AI systems. Scale AI brings together over 90% doctorate holders across 70+ fields to collaborate on high-impact projects that influence how AI is built, evaluated, and governed.

Key responsibilities

Participate in carefully selected AI and machine learning projects that address safety, policy guardrails, and real-world deep learning applications.
Design, review, and optimize machine learning models using modern frameworks to help AI systems understand and perform complex workflows.
Evaluate complex machine learning code and AI-generated implementations to assess efficiency, correctness, and quality.
Collaborate with Scale AI’s research team to co-author technical reports and peer-reviewed research publications.
Contribute to an interdisciplinary community through participation in network events, discussion channels, and virtual sessions.
Select which projects to engage with based on your interests and availability, with flexibility in your schedule and workload.

Requirements

Hold a PhD or postdoctoral research experience in Machine Learning, Computer Science, or a closely 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 familiarity with LLM frameworks and MLOps tools, with LangChain experience being advantageous.
Display a detail-oriented, innovative approach to applied AI research with a strong commitment to collaboration.
Maintain full-time work authorization in your country of residence; visa sponsorship is not available.

What makes this role worth considering

This fully remote fellowship offers flexible engagement with no fixed hours or minimum weekly commitment—most fellows dedicate 10–25 hours per week on their own schedule. You’ll gain access to an unparalleled network of leading researchers and innovators while contributing to published research that enhances your academic visibility and professional standing. The work directly supports critical initiatives in AI safety and governance alongside industry partners including Meta, government agencies, and major enterprises.