Senior Principal Radar Autonomy Engineer

Candidates must possess a Master's or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics, Electrical Engineering, or a related field. A deep understanding of Radar hardware, Radar DSP, Radar machine learning, and Radar testing/performance is essential, along with experience developing low-level data pipelines for machine learning. Knowledge of computer architecture principles and common machine learning/deep learning algorithms is required, as is experience designing, training, and analyzing neural networks for applications like object detection or sensor fusion. Significant software engineering experience, fluency in Python with scientific computing libraries and Python bindings development, and experience with deep learning frameworks like PyTorch are necessary. Experience defining data collection, data curation, and working with large datasets, as well as leadership and mentoring experience, are also required. Bonus points include a proven track record of publications, strong C++/CUDA programming skills, and experience with physical simulation of Radar.