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 Machine Learning Engineer - Online Maps to join Aurora's Maps ML team. The Maps ML team is responsible for providing map data to the Aurora driver in the face of real-time world changes.
In this role, you will:
Lead and Collaborate with other members of the Online Maps autonomy team to improve/ideate and implement perception algorithms that power the Aurora Driver
Research and develop state-of-the art deep learning/machine learning models to improve our perception solutions under challenging and diverse scenarios
Develop novel verification and validation technologies and techniques
Partner with engineers from online maps, simulation, and safety to ensure that online mapping technology is ready for operation with no vehicle operator
Build infrastructure and tests that support critical go/no go decisions for deploying the Aurora Driver
Integrate, test, and deploy production-ready solutions into the production code that powers the Aurora Driver
Required Qualifications
Excellent software engineering skills in Python and/or C++
Extensive experience in any deep learning framework, such as PyTorch
Extensive experience in Computer Vision, Machine Learning, Deep Learning, or other relevant areas of Artificial Intelligence (e.g., as evidenced by industry experience, publication record)
Desirable Qualifications
Relevant industry experience (prior work on self-driving vehicles, autonomy, and/or robotics projects)
Contributions to open source project(s)
Strong track record in any field related to machine learning, as evidenced by top-tier publications
Examples of relevant fields and conferences:
Compensation
The base salary range for this position is $189,000 - $303,000 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.