Senior Machine Learning Engineer (Autonomy Data)

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 Senior Machine Learning Engineer (Autonomy Data)

In this role, you will

• Developing new autonomy performance metrics and/or actor models to serve our use cases

• Support our ML model development workflow, such as data collection, processing and other infrastructure.

• Meet with partners in Motion Planning and Software Validation teams to understand their use case and constraints that will inform our projects and technical approach.

• Work with our sibling team in Core Simulation to add any core functionality required to support our actor models

• Develop tooling for any necessary visualization or extraction of insights from developing and running our models.

• Support your team with code reviews and ideas as part of a collaborative environment.

Required Qualifications

• Motivated and can work independently in a fast paced environment, navigating problem ambiguity and churn.

• CV/ML model building experience (data preparation, training, evaluation)

• Robotics-related domain knowledge. Motion Planning experience strongly preferred, but simulation experience in other domains eg. perception, manipulation, controls etc. will also be considered

• Knowledge of Pytorch or Tensorflow, Jupyter

• 5+ years industry experience in robotics/AV/ML related area.

• MS/PhD with 3+ years may also be considered.

Desirable Qualifications

• Experience deploying ML models in production environments

• Publications in top-tier conferences (not workshops).

The base salary range for this position is $168,000-$252,000 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-KW1

#Mid-Senior