Responsibilities
Contribute to the technical direction of the Perception Architecture team and the broader perception organization.
Design and develop core machine learning components and architectures that enable the perception system to scale and reliably address complex, long-tail driving scenarios.
Drive the initial implementation and prototyping of key architectural decisions, such as handling long tail challenges or long range detection.
Contribute to the improvement of model frameworks, architecture, and data pipelines to eliminate development bottlenecks and accelerate model iteration.
Lead challenging technical topics and build consensus across sister teams (e.g., Actor Detection, Scene Understanding, Tracking) and stakeholders to ensure autonomy-wide alignment.
Qualifications
BS (with 4+ years of experience), MS (with 2+ years of experience), or PhD (with 1+ years of experience) in a perception-related field, such as Robotics, Computer Vision, or Machine Learning.
Extensive experience architecting, training, and evaluating deep learning models for challenging problem spaces.
Track record of driving applied research or engineering projects from conception and experimentation to successful productization.
Strong experience in software engineering, machine learning algorithm design, and building data/metrics pipelines for ML development.
Fluency in Python and hands-on experience with C++.
Experience delivering detection, segmentation, tracking, or other perception solutions for real-time robotic applications, with prior experience in sensor fusion being highly desirable.
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