Senior Machine Learning Engineer, Perception, Autonomous Driving

What you'll do

• Design end-to-end perception solutions for road network detection across diverse driving environments and complex intersections.
• Research and develop deep learning models for lane graph construction and road boundary detection.
• Develop generalizable approaches to support various operational design domains and regional expansions.
• Prioritize data collection and labeling strategies to improve the accuracy of perception systems.
• Utilize data simulation and augmentation techniques to solve extreme driving scenarios.
• Productize perception solutions by meeting specific requirements for safety, latency, and software robustness.

What we're looking for

• PhD with 4+ years, MS with 6+ years, or BS with 8+ years of experience in Computer Science, Computer Engineering, or a related field.
• Hands-on experience developing deep learning and algorithms to solve sophisticated real-world problems.
• Proficiency in using deep learning frameworks such as PyTorch.
• Strong programming skills in Python and/or C++.
• Experience in data-driven development and collaboration with data and ground truth teams.
• 2+ years of technical leadership demonstrating high technical and organizational complexity (preferred).
• Expertise in developing generalizable perception solutions for autonomous driving or robotics using deep learning with cameras (preferred).
• Experience deploying DNN-based solutions to embedded platforms, expertise in Transformers/BEV architectures, or technical publications (preferred).