Senior ML SoC Architect for Hyperscale Data Centers

Meta; Sunnyvale (CA); Hybrid; USD 260,000 - 420,000; Full time

Job summary

Meta is seeking a Machine Learning SoC Architect within the Silicon Engineering organization to define and drive architectural definitions, performance analysis, and pre-silicon modeling for custom ASICs powering Meta's AI/ data center workloads at scale.

The role requires 12+ years in architecture and performance, proficiency in C++/Python for modeling, and collaboration across architecture, RTL, and physical design teams to achieve hyperscale throughput and efficiency targets.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• 12+ years of prior experience in defining and delivering multiple high performance ASICs into production, with focus on architecture definition and performance analysis.
• Experience in ASIC performance modeling, microarchitectural analysis, or pre-silicon simulation for custom silicon or SoC designs.
• Proficiency in C++ and Python for developing simulation models, automation frameworks, and performance analysis tools.
• Experience with performance analysis of data center, AI accelerator, or high-performance computing workloads on custom silicon.
• Experience defining architecture and microarchitectural specifications and driving cross-functional alignment across architecture, RTL, and physical design teams.
• Familiarity with post-silicon performance validation and model-to-hardware correlation methodologies.
• Programming in C or C++ with knowledge of mapping hardware algorithms to efficient C/C++ code.
• Master's or PhD degree in Electrical Engineering, Computer Engineering or related field.
• Domain knowledge in power/performance tradeoffs, ML networks, ML frameworks such as Pytorch.
• Experience building or scaling performance modeling infrastructure for hyperscale data center ASICs, including network, storage, or AI inference accelerator designs.

Responsibilities

• Define and drive architectural definition, performance analysis, and pre-silicon modeling for custom ASICs.
• Own architecture specification and performance modeling methodology and silicon roadmap strategy.
• Collaborate with silicon, RTL, and physical design teams to meet throughput, latency, and efficiency targets.
• Develop simulation models, automation tools, and performance analysis frameworks.
• Address data center, AI accelerator, or HPC workloads on custom silicon.

Skills

Computer Architecture

Microprocessor Architecture

Memory Systems

On-Chip Interconnect

Hardware/Software Partitioning

ASIC Performance Modeling

Pre-Silicon Simulation

C/C++

Python

Data Center Workloads

Cross-Functional Alignment

RTL

Physical Design

Post-Silicon Validation

ML/AI Frameworks

Education

Bachelor's degree

Master's or PhD in EE/CE

Tools

C++

Python

Job description

Meta is seeking a Machine Learning SoC Architect within the Silicon Engineering organization to define and drive architectural definitions, performance analysis, and pre-silicon modeling for custom ASICs powering Meta's AI/ data center workloads at scale.

The role requires 12+ years in architecture and performance, proficiency in C++/Python for modeling, and collaboration across architecture, RTL, and physical design teams to achieve hyperscale throughput and efficiency targets.