Software Engineer - Planner Frameworks Pipeline
At a glance
Mid-level Software Engineering role at Zoox. Foster City · full-time · $177,000–$270,000 base.
techroles summary, based on the employer's posting.
What you'll do
- Improve the cost, reliability and speed of large simulation pipelines that validate self-driving vehicle behavior
- Build production APIs, SDKs and tools so autonomy engineers can run varied behavior checks
- Strengthen machine learning training pipelines used by the autonomous behavior group
- Help shape the framework’s architecture and expand its reliability, efficiency and supported use cases
What you bring
- A computer science degree or related qualification, plus at least six years working in industry
- Experience making large distributed systems more cost-efficient
- Hands-on knowledge of Python, familiarity with C++, and experience with AWS or a comparable cloud provider
- A record of keeping production systems highly available
Who this fits
This hands-on role suits an independent engineer who takes ownership and works with autonomy engineers on off-vehicle validation pipelines. The work centers on large data- and GPU-intensive systems; familiarity with the robotics data lifecycle is preferred, while robotics or autonomous-systems experience is not required. The position is hybrid in Foster City.
From the employer
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.
In this role, you will:
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Improve the cost efficiency, reliability, and performance of our validation and simulation pipelines
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Create production-grade APIs, SDKs, and tools to enable a varied set of validations of autonomous behaviors
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Improve the ML training pipelines supporting the autonomous behavior org
Qualifications
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Bachelor’s degree in Computer Science or related field and 6+ years of industry experience
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Experience optimizing large-scale distributed systems for cost and efficiency
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Experience with AWS or similar providers
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Proficiency with Python and familiarity with C++
Bonus Qualifications
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Exposure to machine learning workloads (training, inference, data generation) from a cost optimization perspective
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Background in algorithmic optimization or performance investigation
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Experience with Ray.io, particularly Ray Core and Ray Data
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