About the position
Aurora's mission is to deliver the benefits of self-driving technology safely, quickly, and broadly to make transportation safer, increasingly accessible, and more reliable and efficient than ever before. The Aurora Driver will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone. At Aurora, you'll solve massively complex problems alongside other passionate, smart people, growing as an expert while broadening your field of knowledge. For Aurora's latest news, visit aurora.tech or follow us on LinkedIn. 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.
Responsibilities
- 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
Requirements
- Excellent software engineering skills in Python and/or C++
- Extensive experience in any deep learning framework, such as PyTorch, JAX, TensorFlow
- 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)
Nice-to-haves
- 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: computer vision (e.g., CVPR, ECCV, ICCV, IJCV), machine learning (e.g., ICML, NeurIPS, JMLR, PAMI), robotics (e.g., RSS, IJRR), graphics (e.g., SIGGRAPH, TOG)
Benefits
- Annual bonus
- Equity compensation
- Benefits package
