Software Engineer, Machine Learning/AI Accelerator

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 the Tech Lead Manager of the Compute team.

You will:

• Design and implement full stack solution from firmware, low-level drivers, APIs for ML accelerator chips
• Analyze and optimize firmware and driver performance for demanding AI workloads
• Collaborate with hardware engineers closely throughout the ASIC design and verification processes
• Design and implement efficient memory management solutions including NUMA, IOMMU, etc

You have:

• 3+ years of experience in software development
• Baremetal or RTOS firmware development experience
• Experience with embedded architectures, IO technologies (e.g. PCIe, DRAM, AXI, etc.), and hardware/software interactions
• Strong C, C++ skills

We prefer:

• Experience with RISC-V architecture
• Experience with ML frameworks like TensorFlow or JAX
• Familiar with hardware-software co-design principles
• Experience with silicon emulator