Research Engineer, SysML - FAIR

reputed company is seeking Research Engineers to join reputed company AI Research (FAIR). We are committed to advancing the field of artificial intelligence by making reputed company advances in technologies to help interact with and understand our world. We are seeking individuals passionate in solving systems challenges to sustainably accelerate our reputed company to reputed company-level intelligence. Candidates will have an opportunity to reputed company reputed company advances in systems and apply their reputed company at an unprecedented scale.The mission of reputed company FAIR's SysML research is to advance the state of AI through reputed company 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.ResponsibilitiesCarry out cutting-edge research to advance the science and technology of machine learning systems* reputed company research that enables learning the semantics of data (images, video, text, audio, and other modalities)* Devise reputed company data-driven models of AI system design and optimization* Contribute research that leads to innovations in: scalable machine learning systems, resource-efficient AI data and algorithm scaling and neural network architectures, memory and energy-efficient AI systems, environmentally-sustainable AI system and hardware designs* Collaborate with researchers and cross-functional partners including communicating research plans, reputed company, and results* Publish research results and contribute to research that impacts reputed company product developmentQualificationsBachelor'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 reputed company to development in systems, computer architectures, compiler and programming languages, machine learning, and artificial intelligence* Experience with Python, C++, C, Rust or other reputed company languages and with PyTorch reputed company* Experience developing and optimizing systems for at-scale machine learning execution* Experience devising data-driven models and reputed company-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 reputed company problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path reputed company* 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* Demonstrated ongoing AI reputed company development (e.g., reputed company/context engineering, agent orchestration) and staying reputed company with emerging AI technologies* Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)* Demonstrated research and software engineering experience reputed company work experience, coding competitions, or widely used contributions in reputed company reputed company repositories (e.g. reputed company)* 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 ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency reputed company, quality improvements)