Research Scientist Intern, AI & Compute Foundation - MTIA SW; PhD
Job in
Menlo Park, San Mateo County, California, 94029, USA
Listed on 2026-10-17
Listing for:
Meta
Apprenticeship/Internship
position Listed on 2026-10-17
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Job Description & How to Apply Below
# Research Scientist Intern, AI & Compute Foundation - MTIA SW (PhD)
Menlo Park, CA Artificial Intelligence+ 8 more Apply nowThe MTIA (Meta Training & Inference Accelerator) Software team is part of the AI & Compute Foundation org. The team’s mission is to explore, develop and help productize high-performance software and hardware technologies for AI at datacenter scale. The team co-optimizes both SW (e.g., algorithms and numerics) and HW (e.g., platform and network) to come up with balanced system design.
To develop new systems, requires understanding performance bottlenecks on existing systems. As a result, the team invests significantly into optimizing AI production models on existing systems. This has resulted in TCO wins for all key AI services.
The team has been developing AI frameworks to accelerate Meta’s DL/ML workloads on the specialized MTIA AI accelerator hardware in a highly performant and flexible way. As part of the AI acceleration software stack, we develop kernel libraries exploiting various hardware architectural features, achieving high performance for our inference and training workloads.
Our team at Meta AI offers twelve (12) to twenty-four (24) weeks long internships and we have various start dates throughout the year.
---## Research Scientist Intern, AI & Compute Foundation - MTIA SW (PhD) Responsibilities
* Develop SW stack with one of the following core focus areas: AI frameworks, compiler stack, high performance kernel development and acceleration onto next generation of hardware architectures.
* Contribute to the development of the industry-leading PyTorch AI framework core compilers to support new state of the art inference and training AI hardware accelerators and optimize their performance.
* Analyze deep learning networks, develop & implement compiler optimization algorithms.
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