Staff Software Engineer, Map Fusion

NextGenEnergyJobs; Mountain View (CA); Hybrid; USD 189,000 - 303,000; Full time

Benefits offered by this job

Annual bonus

Equity compensation

Benefits

Job summary

NextGenEnergyJobs seeks a senior engineer to architect and lead onboard mapping algorithms for dynamic map content updates. You will define real-time compute architectures, partner with Motion Planning, Localization, Perception and Fleet Intelligence to ensure seamless map integration.

The role demands deep expertise in 3D geometry, Bayesian inference, Kalman filtering, and reliable, safety-focused ML deployment on edge systems, with a strong track record of guiding complex projects.

Qualifications

• Extensive professional experience architecting and optimizing high-performance C++ in resource-constrained environments.
• Proficient Python for rapid prototyping and testing of spatial algorithms.
• Deep understanding of 3D geometry, coordinate transforms and spatial data handling at scale.
• Mastery of Bayesian inference and Kalman filtering for probabilistic reasoning.
• Experience leading complex projects and mentoring engineers.
• Background in autonomous vehicles, safety-critical robotics, or edge computing.

Responsibilities

• Architect and lead the technical roadmap for onboard mapping algorithms.
• Define real-time, low-latency compute architectures for map updates from sensor data.
• Collaborate with leaders across Motion Planning, Localization, Perception and Fleet Intelligence.
• Formulate safety cases for ML and fusion methods with deterministic performance.
• Develop graph-centric and geometric algorithms for lanes and drivable surfaces.
• Provide mentorship and conduct design reviews to foster engineering excellence.

Skills

3D geometry

Graph theory

State estimation

Bayesian inference

Kalman filtering

Spline manipulation

Geometric curves

Deep learning spatial

Tools

C++

Python

Job description

At the core of everything we do is our commitment to safety.

Key Responsibilities

• 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.

Requirements

• 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.
• 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.
• Working at Aurora At Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks.
• We believe in-person work increases collaboration, empathy and our ability to lead effectively. As a result, we operate in a hybrid work environment where Aurorans are in office at least 3 days per week.
• Our Careers page provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom .