Machine Learning Fellow (AI)

TL;DR

Machine Learning Fellow (AI): Designing, reviewing, and optimizing PyTorch models to help generative AI systems understand deep learning workflows with an accent on GPU optimization and scaling. Focus on evaluating complex ML code, co-authoring research publications, and improving AI-generated implementations.

Location: Remote (Must be authorized to work in the United Kingdom)

Company

Scale AI provides the high-quality data and full-stack technologies that power the world's leading AI models for enterprises and governments.

What you will do

• Design, review, and optimize PyTorch models to improve deep learning workflows for partnered AI labs.
• Evaluate complex ML code and AI-generated implementations for correctness and efficiency.
• Advise on GPU optimization, scaling strategies, and hardware trade-offs.
• Collaborate with the research team to co-author technical reports and research papers.
• Engage with an interdisciplinary network of leading AI thinkers and innovators.

Requirements

• PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field.
• 1-3+ years of professional experience as a Machine Learning Engineer or Data Scientist.
• Strong proficiency in Python and modern ML frameworks such as PyTorch and TensorFlow.
• Legal authorization to work in the United Kingdom.

Nice to have

• Experience with cloud infrastructure (AWS).
• Proficiency with MLOps tools including Docker and Langchain.

Culture & Benefits

• Flexible schedule with options for 10–40 hour work weeks.
• Opportunity to collaborate with a top-tier global network of engineers and experts.
• Exposure to cutting-edge AI research and pioneering applications in science and technology.
• Competitive project-based compensation.

Hiring process

• Application review on a rolling basis.
• Interview discussing research experience, professional background, and mission alignment.
• Invitation to join the Collective.