Staff Software Engineer to join our Map Fusion team to architect, design, and lead the development of algorithms that allow our vehicles to detect and respond to dynamic environmental changes like construction and emergency vehicles in real-time. This is an exciting opportunity to drive the technical roadmap at the intersection of classical geometric algorithms and modern machine learning to solve high-stakes, real-world safety challenges.
In this role, you will- Architect and lead the technical roadmap for onboard algorithms that update map content dynamically in response to changing scenes (e.g., construction zones, active emergency scenes, and manual traffic directors).
- Define the architecture for real-time, low-latency compute solutions that update maps from sensor data on-the-fly under strict embedded performance and safety constraints.
- Partner closely with leadership and principal engineers in Motion Planning, Localization, Perception, and Fleet Intelligence to align on interfaces and ensure seamless, end-to-end map integration.
- Spearhead the safety case formulation for modern machine learning and classical fusion methods, ensuring rigorous safety and deterministic performance standards are met.
- Oversee the development of graph-centric and geometric algorithms to generate highly accurate local geometry of lane lines and drivable surfaces.
- Provide technical mentorship, conduct rigorous design and code reviews, and foster a culture of engineering excellence within the Map Fusion team.
Required Qualifications- Extensive professional experience architecting, writing, and optimizing high-performance, production-grade C++ in resource-constrained environments.
- Strong proficiency in Python for rapid prototyping, framework development, and testing of complex spatial algorithms.
- Deep, intuitive understanding of 3D geometric reasoning, coordinate transforms, and handling of complex spatial/mapping data at scale.
- Strong mastery of graph theory, network optimization, and practical application of complex search algorithms.
- Demonstrated track record of leading complex technical projects from concept to production, aligning multiple stakeholders, and mentoring other engineers.
Desirable Qualifications(this section is optional)- Deep expertise in Deep Learning architectures (particularly for spatial, temporal, or sensor data) and deploying them safely on real-world systems.
- Mastery of Bayesian Inference, Kalman filtering, or state-estimation techniques for probabilistic reasoning.
- Deep background in Spline Manipulation and geometric curves for path, trajectory, and surface modeling.
- Prior experience in the autonomous vehicle industry, safety-critical robotics, or high-performance edge computing
The base salary range for this position is $189,000 -$303,000 [per year OR per hour]. Aurora's pay ranges are determined by role, level, and location. Within the range, the successful candidate's starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.
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Our commitment to safetyAt the core of everything we do is our commitment to safety. Building best-in-class self-driving technology will take time, and we believe that each employee at Aurora has a role in contributing to safety, every step of the way. Aurora expects commitment to our safety policies from every employee, and seeks candidates who take an active responsibility, can contribute to building an atmosphere of trust, and invest in the organization's long-term success by prioritizing working safely, no matter what.
