Senior ML Accelerator Architect: High-Performance Inference

Waymo LLC; Mountain View (CA); On-site; USD 251,000 - 310,000; Full time

Benefits offered by this job

Discretionary annual bonus

Equity incentive plan

Company benefits

Job summary

Waymo LLC in Mountain View, CA is seeking a seasoned Hardware Architect to lead development of high-performance compute for the Waymo Driver. You will design architectures, simulate solutions and collaborate with cross-functional teams to deliver scalable ML inference hardware.

The role requires a strong track record in CPUs/GPUs/ML accelerators, ML model optimization, and SystemVerilog/HLS experience, with a commitment to safety and reliability in autonomous driving.

Qualifications

• MS degree in Computer Science or Computer Engineering or equivalent practical experience.
• 10+ years designing high-performance architectures - CPUs, GPUs and/or ML accelerators.
• 3+ years experience with ML architectures, acceleration and model optimization.
• Deep knowledge of ML model architectures and their compute characteristics (bottlenecks, optimization opportunities).
• Strong programming and algorithmic problem solving skills.

Responsibilities

• Analyze inference workloads and map them to hardware, proposing novel HW-friendly implementations and projecting performance.
• Build scalable tools for performance modeling and evaluation of inference workloads.
• Work closely with compiler and model developers to influence engineering tradeoffs and future model architectures.
• Architect, simulate and design novel hardware solutions for state-of-the autonomous driving models.
• Interact with cross-functional engineering teams to identify opportunities and realize architectural vision.

Skills

High perf architectures

ML acceleration

Strong programming

Model optimization

Education

MS in CS/CE

Tools

SystemVerilog

HLS

Job description

Waymo LLC in Mountain View, CA is seeking a seasoned Hardware Architect to lead development of high-performance compute for the Waymo Driver. You will design architectures, simulate solutions and collaborate with cross-functional teams to deliver scalable ML inference hardware.

The role requires a strong track record in CPUs/GPUs/ML accelerators, ML model optimization, and SystemVerilog/HLS experience, with a commitment to safety and reliability in autonomous driving.