Step inside the world of self-driving freight, powered by the Aurora Driver. Delivering the benefits of self-driving technology safely, quickly, and broadly. Backed by Greylock, Index and Lightspeed.
About the role
Design, implement and own geometric map-generation algorithms, including sensor optimization, large scale pose-graph optimization and multi-modal alignment, Identify and build a system that will be immune to failure modes. In doing so, be expected to root cause and ship algorithmic fixes with measurable success criteria. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- BS, MS or PhD in Computer Science, Robotics, Electrical Engineering or a related field, or equivalent practical experience
- 6+ years of professional software development experience in C++ with track record of leading technically ambiguous, multi-quarter projects
- Hands-on experience with 3D geometry and point-cloud processing, such as registration (ICP, scan matching), pose-graph or nonlinear least-squares optimization, surface reconstruction or lidar-based SLAM/mapping
- Strong grasp of linear algebra, spatial transforms, numerical optimization and probability
- Experience debugging and improving data quality across large datasets or pipelines
- Experience building HD maps or map-building systems for autonomous vehicles or robotics
More about this role
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 .
Map Build's Geometric Generation team is hiring a Software Engineer to build the 3D spatial foundation that powers the Aurora Driver. You will own the algorithms that process millions of miles of lidar logs into automated offline maps, solving crucial speed and scaling challenges as Aurora expands to new routes.
Design, implement and own geometric map-generation algorithms, including sensor optimization, large scale pose-graph optimization and multi-modal alignment,
Identify and build a system that will be immune to failure modes. In doing so, be expected to root cause and ship algorithmic fixes with measurable success criteria.
Improve the runtime and scalability of large-scale distributed...
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