Meta • Menlo Park, CA 94025
Job #2750229338
Summary:
Meta is seeking a Research Scientist to join our Research & Development teams. The ideal candidate will have industry experience working on AI Infrastructure related topics. The position will involve taking these skills and applying them to solve for some of the most crucial & exciting problems that exist in the hardware/software space for AI Training. We are hiring in multiple locations and across different teams: The Model/System Co-Design team works on (1) optimizing the parallelisms, compute efficiency, training paradigms to improve the scalability and reliability of large scale distributed training systems; (2) innovating and co-designing noval model architecture for sustained scaling and hardware efficiency; (3) co-designing the learning algorithm to improve the efficiency and robustness of training convergence. We have succesfully landed a number of step function changes to both LLM pre-training and ranking/recommendation model co-design, and continue to focus on bleeding edge exploration to achieve industry-leading scale and efficiency.The MTIA Training Performance team is dedicated to maximizing training performance of Generative AI and recommendation models on Meta's custom accelerators. We model and project the performance of current and future training workloads on custom hardware while it is being designed to provide early, crucial feedback to the architecture, compiler, and kernels teams. We employ cutting-edge optimization and data parallelization strategies to maximize training throughput for the next generations of LLMs and deep recommendation models, and we work cross-functionally with many partner teams to assure the end-to-end performance of large-scale training in order to more quickly deliver the next generation of Generative AI experiences to our users.The Collectives and Communication team within AI Co-design helps drive the development, optimization and tuning of Collective Communications libraries for Nvidia GPUs, MTIA accelerators and AMD GPUs covering both AI training and inference use cases. The comms team works to optimize communications performance at scale and investigate improvements to algorithms, tooling, and interfaces that can impact Meta workloads. We actively work in multiple HPC collective communication libraries and collaborate with teams across Meta and externally.
Required Skills:
Research Scientist, Systems ML and HPC - SW/HW Co-Design Responsibilities:
Apply High-Performance Computing (HPC) algorithms and techniques to optimize large-scale AI workloads
Analyze, benchmark, and optimize large-scale workloads on next-generation training superclusters
Apply relevant AI infrastructure and software/hardware acceleration techniques to build and optimize our intelligent ML systems that improve Meta's products and experiences
Influence next-generation model and hardware architecture choices by projecting training performance and model efficiency
Goal-setting related to project impact, AI system design, and infrastructure/developer efficiency
Directly or influencing partners to deliver impact through deep, thorough data-driven analysis
Drive large projects across multiple teams
Define use cases and develop methodology and benchmarks to evaluate different approaches
Apply in depth knowledge of how ML infra interacts with the other systems around it
Experience in systems software development such as collective Communications
Minimum Qualifications:
Currently has, or is in the process of obtaining, a Master's/PhD degree in Computer Science, Computer Vision, Generative AI, NLP, relevant technical field, or equivalent practical experience. Degree requirements must be completed prior to joining Meta
Currently has, or is in the process of obtaining, a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
Specialized experience in one or more of the following machine learning/deep learning domains: high-performance computing, performance optimizations, SW/HW co-design, hardware accelerators architecture, GPU architecture, machine learning compilers, ML systems, AI infrastructure, or machine learning frameworks (e.g. PyTorch), numerics, Collective Communication libraries (NCCL or RCCL), and model compression
Experience developing AI system infrastructure or AI algorithms in C/C++ or Python
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
Preferred Qualifications:
Experience or knowledge of training/inference of large-scale AI models
Experience or knowledge of distributed and cloud systems
Experience or knowledge in one or more of: recommendation and ranking models, LLM and/or LDM, or Collective Communication libraries (NCCL or RCCL)
Public Compensation:
$117,000/year to $173,000/year + bonus + equity + benefits
Industry: Internet
Equal Opportunity:
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at ~~~.
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