META
Research Scientist, Systems ML and HPC - SW/HW Co-Design
META, Menlo Park, California, United States, 94025
Research Scientist, Systems ML and HPC - SW/HW Co-Design
Be one of the first applicants, read the complete overview of the role below, then send your application for consideration. 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 crucial and exciting problems 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:
Optimizing the parallelisms, compute efficiency, and training paradigms to improve the scalability and reliability of large-scale distributed training systems.
Innovating and co-designing novel model architecture for sustained scaling and hardware efficiency.
Co-designing the learning algorithm to improve the efficiency and robustness of training convergence.
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.
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.
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.
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, or a relevant technical field.
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).
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.
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).
Compensation:
$117,000/year to $173,000/year + bonus + equity + benefits.
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, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.
Meta is committed to providing reasonable support (called accommodations) in our recruiting processes for candidates with disabilities, long-term conditions, mental health conditions, or sincerely held religious beliefs.
#J-18808-Ljbffr
Be one of the first applicants, read the complete overview of the role below, then send your application for consideration. 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 crucial and exciting problems 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:
Optimizing the parallelisms, compute efficiency, and training paradigms to improve the scalability and reliability of large-scale distributed training systems.
Innovating and co-designing novel model architecture for sustained scaling and hardware efficiency.
Co-designing the learning algorithm to improve the efficiency and robustness of training convergence.
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.
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.
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.
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, or a relevant technical field.
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).
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.
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).
Compensation:
$117,000/year to $173,000/year + bonus + equity + benefits.
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, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.
Meta is committed to providing reasonable support (called accommodations) in our recruiting processes for candidates with disabilities, long-term conditions, mental health conditions, or sincerely held religious beliefs.
#J-18808-Ljbffr