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# software engineer

- **Company:** Zoox
- **Location:** Foster City, CA, United States
- **Experience:** Expert
- **Salary:** $254,000.0 - $350,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, C++ (Programming Language), Distributed Systems, Python (Programming Language), Machine Learning, System Availability, Kubernetes, Information Technology, Data Generation
- **Published:** September 17, 2026
- **Apply:** https://jobs.lever.co/zoox/4cf378f6-fab9-4bdb-a349-4ae70c099b8e/apply

## About the Role

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., * Bachelor's degree in Computer Science or related field and 8+ years of industry experience

 * Experience optimizing large-scale distributed systems for cost and efficiency
 * Experience with AWS or similar providers
 * Proficiency with Python and familiarity with C++, * Exposure to machine learning workloads (training, inference, data generation) from a cost optimization perspective
 * Background in algorithmic optimization or performance investigation
 * Experience with Ray.io, particularly Ray Core and Ray Data

## 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., * Improve the cost efficiency, reliability, and performance of our validation and simulation pipelines

 * Create production-grade APIs, SDKs, and tools to enable a varied set of validations of autonomous behaviors
 * Improve the ML training pipelines supporting the autonomous behavior org


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