Senior Applied Scientist

About the role

The Senior Applied Scientist will lead the development of perception systems that utilize radar and thermal imaging technologies to enable robots to operate reliably in challenging environments. This role involves developing ML-driven perception pipelines for non-traditional sensing modalities, focusing on extracting semantic and geometric information from radar point clouds, radar tensors, and thermal imagery.

Responsibilities

• Lead the research, design, and development of ML-based perception pipelines for radar and thermal/infrared imaging modalities
• Develop deep learning models for object detection, classification, segmentation, and tracking using radar data (point clouds, range-Doppler maps, radar tensors) and thermal imagery
• Design and implement multi-modal fusion architectures that combine radar, thermal, camera, and depth data for robust, all-condition perception
• Develop novel representations and feature extraction methods tailored to the unique characteristics of radar and thermal sensors (sparsity, noise profiles, spectral properties)
• Build end-to-end perception systems — from raw sensor data processing and calibration to model training, evaluation, and real-time deployment
• Collaborate closely with Hardware, Navigation, Planning, and Controls teams to define sensor configurations and deliver integrated autonomy solutions
• Establish benchmarks, datasets, and evaluation frameworks for radar and thermal perception
• Mentor scientists and engineers; foster a culture of scientific rigor, innovation, and high-impact delivery
• Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents

Qualifications

• Experience programming in Java, C++, Python or related language
• PhD in computer science, electrical engineering, or related field
• 5+ years of hands-on experience in Computer Vision — including object detection, segmentation, tracking, or scene understanding
• Strong expertise in developing and deploying deep learning models for visual perception tasks
• Experience processing and applying ML-based approaches to radar data and/or thermal/infrared imagery
• Strong experience with deep learning frameworks (PyTorch, TensorFlow, or equivalent)
• Proven track record of delivering perception systems from research to production
• Strong publication record in top-tier computer vision, robotics, or ML venues