Drimva

Waymo

Senior Staff Android Engineer, In-Car Experience

$298K–$368K

Mountain View, CA, USA +1 · Senior Staff · Full-time · Posted May 18, 2026

Location
Mountain View, CA, USA
Mountain View, California, United States
Experience
10+ years of professional software engineering experience.
Education
Bachelor’s degree in Computer Science, Electrical Engineering, a related technical field, or equivalent practical experience.

About the job

Leads the technical vision and hands-on development of Waymo’s in-car software platform and rider experiences, spanning Android systems, vehicle integration, and AI-enabled developer workflows.

What you'll do

  • Set architecture and lead integration across vehicle bring-up, Android platform services, and rider-facing applications.
  • Review system designs, troubleshoot platform and performance issues, and establish software reliability standards.
  • Drive AI developer tooling adoption, partner across teams, and mentor senior engineers and tech leads.

What they ask for

  • Bachelor’s degree in Computer Science, Electrical Engineering, a related technical field, or equivalent practical experience.
  • 10+ years of professional software engineering experience, including strategic technical leadership and delivery of large-scale systems.
  • Deep Android/AOSP platform expertise, including system services, HAL, IPC/Binder, and C++ native layers.
  • Experience with modern client architecture, systems programming, Kotlin, Jetpack Compose, distributed backend systems, and AI-native developer workflows.

Nice to have

  • Master’s or PhD in a related field; automotive software, AAOS, or vehicle hardware integration experience.
  • Experience with third-party developer frameworks or SDKs, graphics pipelines, or safety-critical, high-reliability, or low-latency systems.

Pay

$298,000 — $368,000 USD (base salary)

Tools

Android/AOSP, HAL, IPC/Binder, C++, Kotlin, Jetpack Compose, OpenGL ES, Vulkan

AI focus

Champion adoption of AI-native developer tooling, agentic workflows, LLMs, and automated evaluation systems to improve software development velocity and quality.

Model-written summary · the original posting is authoritative

First seen Oct 10, 2026 · Last verified Nov 5, 2026 (UTC)