Staff Software Engineer - Behavior Planning

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’re searching for a Staff Software Engineer, Behavior Planning.

In this role, you will

• Develop real-time robotic algorithms for selecting safe and comfortable trajectories for a self-driving vehicle
• Design, develop, and implement production-grade software in C++ and Python for the Aurora Driver, using modern best practices.
• Contribute to engineering best practices on a large and complex code base. Provide technical leadership for the architectural elements of online and offline systems for evaluating good trajectories.
• Drive ambitious technical projects across behavior planning and autonomy teams.

 

Required Qualifications

• Master’s Degree in Machine Learning, Robotics, Applied Mathematics, or related.
• 5 years of experience with robotics or related. 
• Requires skills and experience to involve:
• Deep domain expertise and strong software engineering experience in the field of autonomous driving.
• Strong programming and software design skills in C++ and Python.
• Expertise with CUDA and PyTorch.
• Demonstrated experience in designing, building, and productionizing motion planning algorithms.
• Demonstrated experience with statistical techniques for machine learning.
• Experience with the development of simulation engines.
• Demonstrated cross-functional team experience in a software engineering environment.
• Demonstrated experience leading complex, cross-functional software engineering projects.
• Demonstrated ability to architect systems that meet strict safety, latency, and reliability requirements.

 

The base [salary OR hourly wage] range for this position is $189,000- 303,000.00 per year.  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.