Developing and deploying motion planning components for next generation self-driving systems in the trucking transportation industry.
Requirements
- 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
- Strong experience in software engineering and algorithm design
- Fluent in C++ and Python
- Experience architecting, training, and deploying machine learned models
- Experience with standard ML toolchain (PyTorch / TensorFlow, training framework, experiment managers, distributed training, ONNX / TensorRT) a plus
- Knowledge of scene-level behavior prediction models a plus
Responsibilities
- Own delivery of motion planning modules that solve on-vehicle problems and deliver for customer needs
- Design, scope, implement, and integrate machine learning or classical 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
- 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
- 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
Other
- Mission-driven mindset and customer-centric obsession to deliver a compelling product
- Ability to work with significant cross-functional interactions
- Strong presentation and communication skills
- U.S. person status, and/or citizenship status may be required
- Residence in the U.S. may be required
- Ability to obtain a U.S. government export license prior to releasing technologies to certain persons
