Machine Learning Fellow - Human Frontier Collective
Conduct applied AI research by designing, evaluating, and optimizing machine-learning models and code, with a focus on PyTorch, GPU performance, and generative AI systems. Requires a PhD or postdoctoral degree and 1–3+ years of ML engineering or data science experience.
About the job
Responsibilities
- Design, review, and optimize PyTorch models.
- Evaluate complex machine-learning code and AI-generated implementations for efficiency and correctness.
- Advise on GPU optimization, scaling, and trade-offs.
- Collaborate with partnered AI labs and platforms on high-impact machine-learning projects.
- Collaborate with a research team to co-author technical reports and research papers.
- Participate in an interdisciplinary community advancing frontier AI.
Requirements
- 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 machine-learning frameworks.
- Detail-oriented, innovative, collaborative mindset with an interest in applied AI research.
Nice-to-haves
- Experience with AWS.
- Experience with Docker.
- Experience with LangChain.
Compensation and Benefits
- Fully remote, 1099 independent contractor opportunity.
- Estimated six-month duration, with potential for extension.
- Flexible schedule of 10–40 hours per week.
- Project pay rates vary based on the project, scope, skill set, and location.
Skills
Python, PyTorch, TensorFlow, AWS, Docker, LangChain, Gpu Optimization, MLOps
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