Senior SoC NPU Architect for Next-Gen AI Hardware

Samsung-Research-America

Mountain View (CA)

On-site

USD 243,000 - 377,000

Full time

14 days+
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Job summary

Samsung Research America seeks an accomplished NPU Architect to lead architecture and micro-architecture work for next generation SoCs. You will own performance, power, and area tradeoffs, collaborating with hardware and software teams across the SOC stack.

The role requires deep expertise in NPU architecture, cycle-accurate modeling, and ML frameworks, with a strong track record in optimizing AI workloads for high efficiency.

Qualifications

  • Bachelor's/Master's/PhD in Electrical/CS or related field.
  • 16+ years of NPU architecture and development experience.
  • Hands-on with cycle-accurate performance and functional models.
  • Experience with CNNs and LLMs.
  • Proficient in Python, SystemC and/or C++.
  • Experience with ML frameworks: TensorFlow, PyTorch, ONNX.
  • Experience with SoC microarchitecture and memory subsystems.
  • Team player with strong communication.

Responsibilities

  • Propose NPU features to boost PPA for next-gen SOC workloads.
  • Model and analyze NPU performance across apps and benchmarks.
  • Develop cycle-accurate NPU performance models linked to silicon.
  • Deliver architecture proposals to design teams and leadership.
  • Map AI use cases to NPU and optimize SW/HW co-design.
  • Collaborate across SOC, drivers, OS, and system teams through documentation.

Skills

NPU architecture
Python
C/C++
CNN/LLM models
ML frameworks

Education

Bachelor/Master/PhD in Electrical/CS

Tools

SystemC
C++
Python
TensorFlow
PyTorch
ONNX

Job description

Samsung Research America seeks an accomplished NPU Architect to lead architecture and micro-architecture work for next generation SoCs. You will own performance, power, and area tradeoffs, collaborating with hardware and software teams across the SOC stack.

The role requires deep expertise in NPU architecture, cycle-accurate modeling, and ML frameworks, with a strong track record in optimizing AI workloads for high efficiency.

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