AI Research Scientist, SysML - FAIR
Location
Boston, MA
Job Type
Full-time
Category
other-general
Posted
June 04, 2026
**Summary:**
Meta is seeking Research Engineers to join Fundamental AI Research (FAIR). We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals who are experienced in solving systems challenges to sustainably accelerate our reach to human-level intelligence. Candidates will have an opportunity to make fundamental advances in systems and apply their ideas at an unprecedented scale.The mission of Meta FAIR's SysML research is to advance the state of AI through open science innovations. We explore, design, and build ML systems and infrastructures at scale with usability, efficiency, and sustainability as design principles. Some aspects of this role include enabling distributed training at an unprecedented scale through advancements and development in training library and authoring components, such as cuBLAS, cuDNN, FlashAttention, training performance a...
Meta is seeking Research Engineers to join Fundamental AI Research (FAIR). We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals who are experienced in solving systems challenges to sustainably accelerate our reach to human-level intelligence. Candidates will have an opportunity to make fundamental advances in systems and apply their ideas at an unprecedented scale.The mission of Meta FAIR's SysML research is to advance the state of AI through open science innovations. We explore, design, and build ML systems and infrastructures at scale with usability, efficiency, and sustainability as design principles. Some aspects of this role include enabling distributed training at an unprecedented scale through advancements and development in training library and authoring components, such as cuBLAS, cuDNN, FlashAttention, training performance a...