Senior Research Engineer, Perception

Job description

Job responsibilities

• Design and implement cutting-edge perception algorithms for autonomous vehicles, focusing on areas such as sensor fusion, 3D object detection, segmentation, and tracking in complex dynamic environments
• Design and implement ML models for real-time perception tasks, leveraging deep neural networks to enhance the perception capabilities of self-driving trucks
• Lead initiatives to collect, augment, and utilize large-scale datasets for training and validating perception models under various driving conditions
• Develop robust testing and validation frameworks to ensure the reliability and safety of the perception systems across diverse scenarios and edge cases
• Conduct field tests and simulations to validate and refine perception algorithms, ensuring robust performance in real-world trucking routes and conditions
• Work closely with the data engineering team to build and maintain large-scale datasets for training and evaluating perception models, including the development of data augmentation techniques

Job requirements

• Master’s or PhD in Electrical Engineering, Computer Science, Robotics, or a related field, with a focus on sensor fusion, signal processing, or machine learning
• At least 5 years of hands-on experience in developing perception systems for autonomous vehicles, with a strong portfolio in LiDAR and camera-based perception, modern perception technologies, and synthetic data…
• Expertise in programming languages and tools critical for high-performance computing and machine learning, including C++, Python, CUDA, TensorFlow, and PyTorch
• Hands-on experience with sensor calibration, vehicle dynamics, and environmental modeling
• Strong foundation in data structures, algorithm design, and complexity analysis specifically tailored to real-time, high-reliability systems
• Experience with deep learning optimization for edge deployment, including quantization, pruning, and knowledge distillation
• Demonstrated ability to publish research findings in top-tier technical journals and conferences