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Research Scientist, AI & Systems Co-Design (PhD)

Meta· Artificial Intelligence
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Menlo Park, CA$122k - $181kFull-timePosted 4w ago

About the role

Research Scientist role focused on co-designing and optimizing AI systems and hardware for datacenter-scale AI workloads, spanning model optimization, AI hardware, and software stack across compute, network, and storage with collaboration across product, infrastructure, and partner teams.

Responsibilities

  • Explore, co-design and optimize parallelisms, compute efficiency, distributed training/inference paradigms and algorithms to improve the scalability, efficiency, and reliability of GenAI and recommendation systems
  • Innovate and co-design novel model deployment techniques for sustained scaling and hardware efficiency during GenAI and recommendation model serving
  • Explore, prototype and productionize highly optimized ML kernels to maximize the utilization and performance of current and future accelerators for Meta’s AI workloads
  • Benchmark, analyze, model, and project the performance of AI workloads against a wide range of what-if scenarios and provide early input to the design of future hardware, models, and runtime, giving crucial feedback to the architecture, compiler, kernel, modeling, and runtime teams
  • Guide Meta’s AI HW requirements and design focusing on performance at System and Silicon levels. Co-design and optimize our AI HW and related software stack for Meta’s future workloads, with technology pathfinding and evaluation of cutting-edge AI systems
  • Lead cross-functional initiatives spanning multiple engineering organizations to drive high-impact technical milestones

Qualifications

  • 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
  • A PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related technical field. (Completed or near completion.)
  • Proven research experience in one or more of the following areas: computer architecture, operating systems, ML systems and kernels, ML compilers, model-system co-design, performance modeling of AI systems, prevailing accelerators/silicon architectures, ML training algorithms
  • Hands-on proficiency with end-to-end AI hardware architecture or on-device mapping algorithm development, encompassing logic, architecture, and optimizations for performance, power, and area (PPA)
  • Theoretical background and practical experience with AI models (e.g., Transformers, LLMs, Diffusion models, CNNs, Recommendation Models)
  • Experience in system-level performance analysis, profiling, and benchmarking of AI workloads
  • Experience in Python, including developing production-quality code or research prototypes and experience with at least one major AI framework
  • Track record of publishing research papers at peer-reviewed conferences or journals, and experience in communicating technical results to cross-functional stakeholders

Skills

Required:Parallelism optimizationModel deployment techniquesML kernel optimizationPerformance benchmarkingAI hardware collaboration

Benefits

  • Bonus
  • Equity
  • Benefits
Last updated Oct 23, 2026. Interested? Apply on the company site.

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