Staff ML Accelerator Architect

What you'll do

• Analyze inference workloads, map them to hardware, and project performance.
• Build tools to model and evaluate inference performance; collaborate with compiler and model developers on engineering tradeoffs.
• Architect, simulate, and design hardware solutions for autonomous-driving models, working with cross-functional teams.

What they ask for

• M.S. in Computer Science or Computer Engineering, or equivalent practical experience.
• 10+ years designing or architecting complex, high-performance architectures, including CPUs, GPUs, and/or ML accelerators.
• 3+ years of experience with machine-learning architectures, acceleration, and model optimization.
• Deep knowledge of ML model architectures and compute characteristics; strong programming and algorithmic problem-solving skills.

Nice to have

• Track record delivering novel hardware-software solutions that improve ML inference performance and efficiency; ability to lead cross-functional teams.
• Familiarity with semiconductor technologies and tradeoffs across the hardware stack; experience with microarchitecture design using SystemVerilog or HLS.

Pay

$251,000–$310,000 USD base salary

Tools

CPUs, GPUs, ML accelerators, SystemVerilog, HLS

AI focus

Accelerates machine-learning inference for autonomous-driving models through workload analysis, hardware mapping, performance modeling, and hardware architecture design.