Zoox
Senior/Staff Software Engineer - Planner Frameworks Pipeline
Foster City, CA · On-site · Senior
- Discipline
- Software
- Industry
- Automotive
Spec sheet
Automatically summarized from the employer’s posting. Check the original description below for full requirements.
Software
Senior/Staff Software Engineer needed to build and operate large-scale simulation pipelines for validating Zoox self-driving vehicle behavior. Role focuses on data/GPU-heavy workloads using Ray.io and Kubernetes, with ownership of framework architecture, reliability, and efficiency; remote collaboration with autonomy engineers and on-vehicle algorithms.
Day shift
Required
- software engineering
- large-scale simulation pipelines
- Ray.io
- Kubernetes
- data and GPU intensive workloads
- production systems reliability / high availability
- autonomy / robotics familiarity optional
Preferred
- experience with robotics or autonomous systems understanding of robotic data ...
- ownership of framework architecture and performance tuning
- experience with distributed systems and orchestration
Employer description
Zoox is looking for an experienced software engineer to work on large-scale simulation pipelines used to validate the behavior of the Zoox self-driving vehicle. These are data and GPU intensive workloads built on Ray.io and Kubernetes. Given the massive scale and criticality of these pipelines, ensuring their reliability and efficiency has a significant impact on the company’s ability to safely and quickly iterate on autonomy development.
We are a small, scrappy team within the larger Autonomy organization. Although this role primarily involves off-vehicle pipelines, you will work closely with engineers developing the on-vehicle algorithms and models in our autonomy stack. We stay close to the end users - autonomy engineers - and think about the end to end use case for these validation pipelines.
This is a hands-on role with a high degree of independence and ownership. You will be expected to contribute towards the framework’s architecture, reliability, efficiency, and grow its capabilities to support new use cases. You should have a track record of keeping production systems running with high availability. Experience with robotics or autonomous systems is not required but an understanding of the robotic data lifecycle is preferred.
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