Edge ML Software Engineer (system Modeling-pico) - San Jose

ByteDance ByteDance · Big Tech · San Jose, CA · R&D

Develop transaction-level models of edge NPU architectures for ML workloads (CNNs, Transformers) to simulate execution, analyze performance, and optimize for latency, memory, and power targets. Requires strong C/C++ and System C proficiency, computer architecture understanding, and experience with ML accelerator modeling.

What you'd actually do

  1. Develop transaction-level models of edge NPU architectures with bit accuracy and approximate timing/power accuracy, which model compute units, interconnects, memory hierarchies, and data movements, to simulate execution of representative ML workloads of both CNNs and Transformers.
  2. Analyze ML model compute intensity, memory footprint and bandwidth requirements, and operator-level latency.
  3. Collaborate with compiler and algorithm teams to optimize ML workload for latency, memory and power targets.

Skills

Required

  • Computer architecture
  • Electronic system modeling
  • C/C++
  • System C
  • ML workloads analysis

Nice to have

  • Performance and power models for ML accelerators
  • Performance bottleneck analysis
  • Architectural recommendations

What the JD emphasized

  • ML workloads
  • edge NPU architectures
  • ML accelerators

Other signals

  • ML workloads
  • NPU architectures
  • edge ML