<p>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 passionate 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.</p> <p>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 acceleration through hardware-software co-design.Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Master's degree in the field of Computer Science, Computer Engineering, or equivalent practical experience. 4+ years of domain-specific industry experience in areas related to development in systems, computer architectures, compiler and programming languages, machine learning, and artificial intelligence. Experience with Python, C++, C, Rust or other related languages and with PyTorch framework. Experience developing and optimizing systems for at-scale machine learning execution. Experience devising data-driven models and real-system experiments and design implementation for AI system optimization. Experience with scalable machine learning systems, resource-efficient AI data and algorithm scaling, or neural network architectures. Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward. Experience working and communicating cross functionally in a team environment. PhD in the field of Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences such as MLSys, ISCA, ASPLOS, HPCA, PLDI, CGO, NeurIPS, ICML, ICLR, or similar. Demonstrated research and software engineering experience via work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).</p>