Machine Learning Fellow - Human Frontier Collective

• Get invited to engage in high-impact projects with our partnered AI labs and platforms
• Help models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models
• Evaluate complex ML code and AI-generated implementations for efficiency and correctness
• Advise on GPU optimization, scaling, and trade-offs
• Collaborate with Scale’s research team to co-author technical reports and research papers

• PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field
• 1-3+ years of experience as a Machine Learning Engineer or Data Scientist
• Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow)

Experience with cloud infrastructure (AWS) and MLOps tools (Docker, Langchain)

• Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research, while deepening their AI expertise, strengthening analytical and problem-solving skills, and engaging with pioneering AI applications in science and technology
• Join a Top-Tier Network: Collaborate with a global network of engineers and experts to advance responsible AI through impactful, flexible research and training
• Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments