Machine Learning Fellow - Human Frontier Collective (uk)

Scale AI Scale AI · Data AI · Remote · Human Frontier Collective

This role is for a Machine Learning Fellow focused on designing, evaluating, and interpreting advanced generative AI systems. The fellow will work on ML projects, contribute to research publications, and engage with a community of AI researchers. The role involves optimizing PyTorch models, evaluating ML code, advising on GPU optimization, and collaborating on research papers.

What you'd actually do

  1. Get invited to engage in high-impact projects with our partnered AI labs and platforms.
  2. Help models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and advising on GPU optimization, scaling, and trade-offs.
  3. Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., [_SciPredict_](https://scale.com/research/scipredict), [_PropensityBench_](https://scale.com/research/propensitybench), [_Professional Reasoning Benchmark_](https://scale.com/research/prbench)).

Skills

Required

  • Python
  • PyTorch
  • TensorFlow
  • designing PyTorch models
  • evaluating ML code
  • advising on GPU optimization, scaling, and trade-offs
  • collaboration

Nice to have

  • AWS
  • Docker
  • Langchain
  • MLOps tools

What the JD emphasized

  • 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.

Other signals

  • designing, reviewing, and optimizing PyTorch models
  • evaluating complex ML code and AI-generated implementations
  • advising on GPU optimization, scaling, and trade-offs
  • co-authoring technical reports and research papers