Machine Learning Software Engineer, Motion 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 Machine Learning Software Engineer for our Motion Planning Team.

In this role, you will

• Build machine learning approaches for motion planning for creating, generating, and selecting comfortable and safe trajectories for a self-driving vehicle

• Develop policies and plans to manage multi-actor interactions and plans under uncertainty

• Develop approaches that interleave motion planning with forecasting of other agents

• Develop and implement production-grade algorithms for the Aurora Driver

Required Qualifications

• BS, MS, or PhD in Robotics, Machine Learning, Applied Mathematics, Computer Science or related field

• 1+ years of industry experience building software in a production environment

• Strong programming and software design skills ideally in C++ and/or Python

• Knowledge of classical and modern ML approaches such as transformer networks, linear models, recurrent models, convolutional neural networks

• Familiarity with modern ML and GPU toolkits such as PyTorch, TensorFlow, JAX, TensorRT, and/or CUDA

Desirable Qualifications

• Experience with imitation and reinforcement learning and how machine learning can be used in robotics applications

• Experience in designing, building, and productionizing robotics systems, especially decision making systems, motion planning algorithms, state estimation algorithms, probabilistic modeling, or statistical techniques

The base salary range for this position is $144K - $216K 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.

#LI-JL261

#Mid-Senior