Autonomy Platform Engineer

DoorDash•San Francisco, CA

35d•Hybrid

About The Position

DoorDash Labs is an independent team within DoorDash focused on exploring robotics and automation to transform last-mile logistics. The Autonomy Platform Engineer will build and evolve the foundational software that runs the autonomy stack across robot and compute platforms. This role involves working with embedded Linux, compute and sensor enablement, robotics middleware, process orchestration, data capture and replay, system observability, and performance. The engineer will develop production software and tooling to assist autonomy engineers in hardware bring-up, reliable service deployment, failure diagnosis, and system performance validation across robot generations. This position requires close collaboration with autonomy, firmware, electrical, hardware, manufacturing, and validation engineers and reports to the Autonomy Platform Lead. The role is expected to be hybrid, with a mix of in-office and remote work.

Requirements

Strong production C++ and Python experience.
Experience with embedded Linux, robotics, autonomous vehicles, or complex mechatronic systems.
Solid understanding of several of these areas: operating systems, concurrency, networking, middleware, drivers, GPU acceleration, storage, or real-time performance.
Experience debugging complex problems across multiple software and hardware layers.
Experience with profiling, tracing, observability, automated testing, and CI.
Familiarity with Bazel, Git, and modern software-development practices.

Nice To Haves

ROS/ROS2 or comparable robotics middleware experience is preferred.
Experience collaborating in multi-disciplinary teams spanning software, controls, and hardware, and can communicate technical details across domains effectively.

Responsibilities

Build and maintain core runtime, middleware, and platform services used by autonomy applications.
Enable new compute, camera, lidar, and other sensor platforms.
Improve process orchestration, messaging, configuration, startup and shutdown behavior, resource isolation, and fault recovery.
Develop system observability, tracing, performance measurement, diagnostics, and regression-detection capabilities.
Build reliable data capture, replay, and debugging workflows.
Create provisioning, packaging, deployment, integration-test, and platform-readiness tooling.
Lead complex debugging across application, middleware, OS, driver, networking, timing, and hardware boundaries.