Senior Principal Engineer

Senior Principal Radar Autonomy Engineer

We are looking to add a talented Senior Principal Radar Autonomy Engineer to join our Autonomy team. You will own developing state-of-the-art Radar systems, including hardware design, data processing, and developing machine learning models to ingest low-level radar data. You will work closely with a cross functional team to enable the entire sensor suite to empower end-to-end machine learning. As a hands-on engineering lead you will architect and co-develop both Radar sensors and machine learning pipelines to drive our next generation vehicles. Your deep applied research experience will inform your visionary approach to enable more intelligent, capable, and cost effective autonomous vehicles, and your deep engineering experience will enable pragmatic trade-off decisions. We are looking for someone that knows how to push the boundary of “the box”, and thrives working as the technical expert across both the hardware and software domains.  Does this sound like you?

What you'll be doing:

• Applied research and development of deep neural networks for end-to-end solutions.
• Own and deliver state-of-the-art Imaging Radar hardware and machine learning to push the performance boundaries for next generation Autonomous Vehicles.  
• Develop core deep learning codebase for efficient training and testing pipelines.
• Conduct deep learning experiments, write reports / publications, and file patents.
• Work cross functionally with high performance compute, systems, vehicle engineering, autonomy, and suppliers as the end-to-end Radar owner and domain expert to architect and define an optimal sub-system.
• Use your top-notch development expertise to inspire others to develop better practices and principles.
• Mentor junior researchers by providing guidance on research projects and design document reviews.

What we're looking for:

• Masters or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics, Electrical Engineering or a related field.
• Deep understanding of Radar hardware, Radar DSP, Radar machine learning, and Radar testing/performance that informs optimal machine learning performance.  
• Experience developing low-level data pipelines to enable industry leading machine learning performance. 
• Understanding of computer architecture principals and how data pipelines and machine learning algorithms map onto hardware. 
• In-depth understanding of common machine learning and deep learning algorithms (e.g. for classification, regression, and clustering).
• Experience designing, training, and analyzing neural networks for at least one of the following applications: object detection, image segmentation, sensor fusion, multitask learning, motion prediction, and/or tracking.
• Significant experience with software engineering principles including software design, source control management, build processes, code reviews, testing methods.
• Fluency in Python, including standard scientific computing libraries and Python bindings development experience.
• Experience with PyTorch or other deep learning frameworks.
• Experience defining data collection, data curation, and working with large data sets.
• Leadership and mentoring experience.

Bonus points (not required):

• Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.)
• Strong programming skills in C++ and/or CUDA programming
• Experience with physical simulation of Radar and other sensors.

Why you should join us:

• Join a world-class team of engineers including inventors of nuScenes (https://www.nuscenes.org), PointPillars (https://arxiv.org/abs/1812.05784), PointPainting (http://arxiv.org/abs/1911.10150), ADCNet (https://arxiv.org/pdf/2303.11420), and AAETR (https://arxiv.org/pdf/2408.09362).
• Lead an end-to-end Imaging Radar & machine learning development to set a new performance benchmark for what is possible.
• Design and implement the system the right way.
• Speaking and publication opportunities are encouraged and supported.