Software Engineer, Planner Architecture
Confirmed live in the last 24 hours
Aurora Innovation
Compensation
$126K - $181
Job Description
Who we are
Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.
The Aurora Driver will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone.
At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit aurora.tech or follow us on LinkedIn.
Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We are looking for a Software Engineer to partner with our Planner Architecture team on this exciting journey. The Planner Architecture Team owns the software framework and systems integration that houses Aurora's core motion planning algorithms on the vehicle. The team defines and drives the world representation, data structures, and APIs for the Motion Planner, ensuring software quality, robustness, and real-time performance through continuous latency burn-down and architectural optimization. The team also develops the specialized tooling and infrastructure required to identify suboptimal on-road driving behaviors, enabling rapid diagnosis and data collection to improve the Aurora Driver.
In this role you will:
- Collaborate within the Autonomy Integration group and with stakeholders across various autonomy subsystems to drive cross-functional design and implementation.
- Develop software that directly influences the on-road behavior of autonomous vehicles, including architecting the framework and interfaces that core Motion Planning algorithms integrate into.
- Build onboard infrastructure for detecting and capturing interesting scenarios and anomalous behaviors to accelerate the improvement of the autonomy stack.
- Enhance Planner robustness and maintainability by reducing faults and improving the flexibility, composability, and testability of the system.
- Architect and optimize code paths to minimize latency in safety-critical components, ensuring the Planner meets real-time constraints.
- Improve the Planner’s world representation and data encoding to support both learned and engineered planning approaches.
- Expertise in Modern C++, specifically for latency-sensitive and safety-critical applications.
- 2+ years of applied in
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