The partner company is looking to solve complex, less-defined problems in autonomous vehicle technologies, focusing on scene understanding, behavior prediction, and motion planning, to guide safe and efficient robotaxi operations.
Requirements
- Strong expertise in Machine Learning and Deep Learning algorithms.
- Experience designing, training, and analyzing neural networks for applications such as motion planning, object detection, sensor fusion, motion prediction, or multi-object tracking.
- Advanced knowledge of software engineering principles, including code reviews, source control, testing, and build processes.
- Proficiency with PyTorch or other Python-based deep learning frameworks.
- Experience working with large datasets and deriving actionable insights.
- Strong problem-solving skills with the ability to execute efficiently in less well-defined situations.
- Bonus: publications in relevant conferences, experience in autonomous vehicles, deploying models in real-world environments, and programming skills in C++ and/or CUDA.
Responsibilities
- Design, train, evaluate, and deploy ML models for scene understanding, behavior prediction, and planning.
- Develop and implement experiments to improve model performance and robotaxi capabilities.
- Analyze offline and on-road data to guide major model updates.
- Maintain a high-quality training and evaluation codebase, including dataset generation and evaluation pipelines.
- Stay updated with the latest ML and deep learning research, proposing new architectures and network designs.
- Mentor and collaborate with team members, fostering knowledge sharing and technical excellence.
Other
- Master’s or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics, or related field; or equivalent industry experience.
- Occasionally travel and coordinate work across multiple time zones.
- Opportunities to work remotely within the United States with occasional travel.
