Job description

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo's Compute Team is tasked with a critical and exciting mission: We deliver the compute platform responsible for running the fully autonomous vehicle’s software stack. To achieve our mission, we architect and create high-performance custom silicon; we develop system-level compute architectures that push the boundaries of performance, power, and latency; and we collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance. We are a multidisciplinary team seeking curious and talented teammates to work on one of the world’s highest performance automotive compute platforms. This role follows a hybrid work schedule and you will report to a Software Engineering Manager. You will: Leverage agentic AI to accelerate analysis, planning and implementation of production software improvements Analyze the performance characteristics of code generated by our production grade compiler, and design and implement optimizations to improve that performance Design and implement compiler support for novel features of our high-performance architecture Work with hardware architects to understand and influence the development of our unique neural network inference platform through hardware/software codesign Work with model developers to tune their neural networks for better inference efficiency and accuracy You have: BS degree in Computer Science/Electrical Engineering or equivalent experience and 5+ years of industry experience OR MS degree in Computer Science/Electrical Engineering and 3+ years of industry experience PhD degree in Computer Science/Electrical Engineering and 1+ years of industry experience 3+ years experience working on compilers for parallel architectures 1+ years experience working with ML inference or linear algebra computation C++ programming skills, including leveraging agentic AI acceleration We prefer: Python programming experience Experience with compilers for neural networks, especially MLIR-based Knowledge of computer architectures used for neural network inference, and neural network performance characteristics Knowledge of the principles behind popular machine learning and neural network algorithms and applications The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $213,000 — $263,000 USD

Requirements

Must-haves

This role follows a hybrid work schedule and you will report to a Software Engineering Manager.
Leverage agentic AI to accelerate analysis, planning and implementation of production software improvements
Analyze the performance characteristics of code generated by our production grade compiler, and design and implement optimizations to improve that performance
Design and implement compiler support for novel features of our high-performance architecture
Work with hardware architects to understand and influence the development of our unique neural network inference platform through hardware/software codesign
Work with model developers to tune their neural networks for better inference efficiency and accuracy
BS degree in Computer Science/Electrical Engineering or equivalent experience and 5+ years of industry experience OR
MS degree in Computer Science/Electrical Engineering and 3+ years of industry experience
PhD degree in Computer Science/Electrical Engineering and 1+ years of industry experience
3+ years experience working on compilers for parallel architectures
1+ years experience working with ML inference or linear algebra computation
C++ programming skills, including leveraging agentic AI acceleration
Python programming experience
Experience with compilers for neural networks, especially MLIR-based
Knowledge of computer architectures used for neural network inference, and neural network performance characteristics
Knowledge of the principles behind popular machine learning and neural network algorithms and applications

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlpythonmachine learning

Platform: greenhouse
Effort: quick