Role overview

This is a Machine Learning Fellowship with the Human Frontier Collective (HFC), a network of researchers and domain experts dedicated to advancing frontier AI systems. As a fellow, you’ll join an interdisciplinary community of over 90% doctorate holders spanning 70+ fields, working on high-impact AI and machine learning projects while contributing to published research.

Key responsibilities

Participate in carefully selected AI and ML projects that may include evaluating AI models, designing experiments, and building reinforcement learning environments.
Help frontier AI systems understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models.
Evaluate complex machine learning code and AI-generated implementations for efficiency, correctness, and best practices.
Contribute to building AI safety and policy guardrails for advanced systems.
Co-author technical reports and research papers with Scale’s research team to advance published knowledge in the field.
Engage with the collective 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 possess senior industry experience in Machine Learning or a related discipline.
Demonstrate 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.
Possess familiarity with LLM frameworks such as LangChain and MLOps tools.
Display a detail-oriented and innovative approach to applied AI research with a genuine commitment to collaboration.
Hold or independently obtain full-time work authorization in your country of residence, as visa sponsorship is not provided.

What makes this role worth considering

This fully remote position offers flexibility with no fixed minimum hours—most fellows contribute 10–25 hours per week on a schedule they set. You’ll work alongside leading researchers and thought leaders across diverse fields while gaining visibility through co-authored publications and building your professional network within an exclusive, highly credentialed community.