Machine Learning Fellow - Human Frontier Collective (US)
Collaborate on high-impact AI research projects, design and review deep learning models in PyTorch, analyze GPU performance, and co-author publications. Requires PhD in CS/AI/ML and hands-on expertise with Transformers, CNNs, and diffusion models.
About the job
About the Program
The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to design, evaluate, and interpret advanced generative AI systems.
What You’ll Do
- Collaborative Work: Engage in high-impact projects with partnered AI labs. Design and review advanced deep learning problems, analyze and critique complex ML code and AI-generated PyTorch implementations. Apply expert judgment on GPU performance, profiling, and hardware-aware architecture and scaling trade-offs.
- HFC Community: Become part of a supportive, interdisciplinary network of innovators and thought leaders.
- Contribute to Research Publications: Collaborate to co-author technical reports and research papers.
Who Should Apply
- Advanced degree (PhD or higher) in Computer Science, Electrical/Computer Engineering, Applied Math, AI/ML, or a related field.
- Hands-on experience building and fine-tuning deep learning models in PyTorch, including architectures like Transformers, CNNs, and diffusion models.
- Familiarity with GPU performance and optimization, including memory management, CUDA kernels, and profiling tools.
- Skilled at analyzing research-level model code and giving clear, actionable feedback.
- Able to clearly explain complex ML behaviors and trade-offs.
Why Join the HFC?
- Professional Development: Expand influence through review projects, advisory roles, and research.
- Flexible Schedule: 10–40 hour weeks that fit around your life.
- Competitive Pay: Up to $80/hr, based on experience, skills assessment, and location.
Skills
PyTorch, Transformers, Cnns, Diffusion Models, CUDA, Gpu Optimization, Deep Learning, Machine Learning, Model Fine-Tuning, Profiling Tools
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