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Research Scientist, Systems ML - HW/SW Co-Design

Meta· Artificial Intelligence
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Menlo Park, CA$184k - $257kFull-timePosted 1mo ago

About the role

Research Scientist for the AI & Systems Co-Design team focused on hardware/software co-design for next-generation AI accelerators, translating production ML workload insights into architectural decisions to improve performance, power efficiency, and cost at hyperscale. Collaborates with silicon design, ML infrastructure, and product teams to ensure hardware aligns with future AI workloads.

Responsibilities

  • Shape MTIA's architecture: Translate production ML workload insights into hardware design decisions that improve performance, power efficiency, and cost across Meta's next-generation AI accelerators
  • Drive pre-silicon decision-making: Lead deep, data-driven analysis of hardware micro-architectures, building the performance models and benchmarks that inform silicon investment decisions
  • Build evaluation infrastructure: Develop tooling and frameworks for comparative architecture studies, enabling rapid exploration of design trade-offs before committing to silicon
  • Operate cross-functionally at scale: Drive large initiatives spanning silicon design, ML infrastructure, and product teams, ensuring hardware roadmap decisions are grounded in real workload needs
  • Define the methodology: Establish use cases, benchmarks, and evaluation criteria that become the standard for how Meta assesses hardware architecture options
  • Bridge ML and hardware: Apply deep knowledge of how ML infrastructure interacts with accelerator hardware, networking, and memory systems to drive novel architectural innovations
  • Elevate the team: Mentor research scientists and engineers within the team and across partner teams, establish and uphold documented standards for technical rigor (e.g., code review, reproducibility, benchmarking methodology), and promote technical rigor and innovation grounded in production impact

Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field
  • 7+ years of industry experience (or equivalent)
  • Experience in one or more of the following: hardware/software co-design, AI accelerator architecture, systems for ML, high-performance computing, or performance modeling
  • Experience with power, performance, and area (PPA) trade-offs in hardware micro-architecture design
  • Understanding of modern ML workloads (large language models, generative AI) and how hardware architecture choices impact their performance at scale
  • Experience contributing to at least one silicon tapeout, from architectural exploration through pre-silicon validation
  • Experience with AI system design, including networking, host-to-device ratios, and power trade-offs

Skills

Required:Hardware/software co-designPPA trade-offsML workload understandingsilicon tapeout experienceAI system design

Benefits

  • benefits information implied via posting (benefits available at Meta) — specific items not enumerated in the description
Last updated Oct 23, 2026. Interested? Apply on the company site.

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