Research Scientist Intern - AI Systems and Infrastructure
MetaAdded 1d ago
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Quick summaryby newgrad.ai
What you'll do
- Develop systems for large-scale AI training, inference, and evaluation.
- Conduct end-to-end research projects from problem framing to publication.
- Work on hardware-software co-design, cluster scheduling, and resource management.
What they're looking for
- Ability to drive independent research projects with mentorship.
- Interest in improving AI research efficiency and predictability.
- Availability for internships lasting 12 to 24 weeks.
Meta Fundamental AI Research (FAIR) is looking for Research Scientist Interns to rethink the systems that power frontier AI research. AI workloads are changing faster than the infrastructure beneath them: large-scale training, inference, evaluation, and autonomous AI agents now compete for the same accelerators. Many of the resulting questions about how to share, schedule, and operate compute at scale have no established answers.
Our team works across the stack, from hardware-software co-design and performance modeling to cluster scheduling, resource management, and the infrastructure needs of agentic AI. The goal is to make AI research faster, more efficient, and more predictable at any scale.
In this role you will embed with a world-class, multi-disciplinary team of research scientists and engineers to pursue an open research question end to end- from problem framing through experimentation to publication. Interns are expected to drive their own project with mentorship, not execute a predefined task list. Our internships are twelve (12) to twenty four (24) weeks long, and we have various start dates throughout the year.
From Meta's public posting, laid out for reading by newgrad.ai with the wording unchanged. Check the original before you apply.
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