Staff Software Engineer, Online Maps

Aurora•Mountain View, CA

2d•Hybrid

About The Position

Aurora is seeking a Staff Machine Learning Engineer to join its Maps ML team, which provides map data to the Aurora Driver in response to real-time changes in the world. The role works with the Online Maps autonomy team to develop and improve perception algorithms and machine learning solutions for challenging, diverse scenarios. It also involves developing verification and validation techniques, partnering with online maps, simulation, and safety engineers to prepare online mapping technology for operation without a vehicle operator, and building infrastructure and tests that support deployment decisions. The engineer will integrate, test, and deploy production-ready solutions into the code powering the Aurora Driver. Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly. Aurora expects employees to prioritize safety and values integrity, ambitious goals, collaboration, and inclusion. Employees are expected to work from the office at least three days per week; some roles may require up to five days per week based on operational needs. The base salary range is $189,000–$303,000 per year. The successful candidate is also eligible for an annual bonus, equity compensation, and benefits. Starting base pay depends on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions.

Requirements

Excellent software engineering skills in Python and/or C++.
Extensive experience with a deep learning framework such as PyTorch.
Extensive experience in computer vision, machine learning, deep learning, or another relevant area of artificial intelligence, demonstrated through industry experience, publications, or other evidence.

Nice To Haves

Relevant industry experience, such as prior work on self-driving vehicles, autonomy, and/or robotics projects.
Contributions to open-source projects.
A strong track record in a field related to machine learning, demonstrated by top-tier publications. Relevant fields and venues include computer vision (CVPR, ECCV, ICCV, IJCV), machine learning (ICML, NeurIPS, JMLR, PAMI), robotics (RSS, IJRR), and graphics (SIGGRAPH, TOG).

Responsibilities

Lead and collaborate with 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 and machine learning models to improve perception solutions across challenging and diverse scenarios.
Develop novel verification and validation technologies and techniques.
Partner with engineers from online maps, simulation, and safety to ensure online mapping technology is ready for operation without a 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.