Compute Workload Specialist

Waymo • Mountain View, CA

1d • Hybrid

About The Position

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. In this hybrid role, you will report to a Software Engineering Manager

Requirements

• MS degree in Computer Science or Computer Engineering
• Proficiency in C++
• In-depth knowledge of compute architecture, compiler, and operating system
• A minimum of five years of professional or research experience in performance analysis and optimization

Nice To Haves

• GPGPU/accelerator programming
• Knowledge of ML algorithms and their numerical properties.
• Experience with software engineering in edge computing especially in autonomous vehicle

Responsibilities

• Identify important compute workloads for autonomous vehicles and understand their performance characteristics
• Develop and maintain tests and tools for numerical correctness, become the main expert on ML numerics
• Implement optimizations in compute workloads for the current and next-generation hardware/software stack
• Build benchmarks and reduced workload applications to prototype and stress test the next-generation hardware/software stack
• Collaborate with the broader software organization to ensure optimal and efficient use of next-generation compute platforms
• Interact with hardware teams to provide key results and insights over the next-generation hardware design and decision making

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees