Staff Software Engineer - Motion Planning ML

October 6

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Description

• Own delivery of motion planning modules that solve on-vehicle problems and deliver for customer needs - meeting product requirements and meeting the needs of the controls system, providing a safe, smooth trajectory for the system to follow. • Design, scope, implement, and integrate machine learning systems to solve on-vehicle behavior problems in a real-time, resource-constrained environment. • Provide input in the technical direction for the team, and work cross-functionally to develop safe systems. This will include working closely with other teams such as perception, localization, and controls to ensure that the input to the motion planning modules is appropriate. • Work closely with systems engineers to ensure a safe, well tested product is delivered. • Work closely with verification teams to ensure proper testing and validation of the motion planning modules. Make extensive use of unit testing, simulation, and log simulation to properly validate their work. • Spend time on the vehicles to experience in person the efforts being worked. • Provide input to team roadmaps and ensure product features are properly prioritized. • Identify bottlenecks and limitations in system performance, and develop novel motion planning components to unlock new capabilities and ensure a reliable system. • Be involved in experimentation, design and iteration exercises, and help to align stakeholders by using strong presentation and communication skills.

Requirements

• Experience architecting, training, and deploying machine learned models. • Joint prediction-planning models. • Motion planning models. • Experience building motion planning systems for real world applications with a strong understanding of the pros and cons of various approaches. • Knowledge and experience with real-time algorithms, and machine learning approaches. • Strong experience in software engineering and algorithm design. • Fluent in C++ and Python. • Experience with standard ML toolchain (PyTorch / TensorFlow, training framework, experiment managers, distributed training, ONNX / TensorRT)