Plus is a global provider of highly automated driving and fully autonomous driving solutions with headquarters in Silicon Valley, California. Named by Forbes as one of America’s Best Startup Employers and Fast Company as one of the World’s Most Innovative Companies, Plus’s open autonomy technology platform is already powering vehicles in commercial use today. Working with one of the largest companies in the U.S., vehicle manufacturers, and others globally, Plus is helping to make driving safer, more comfortable, and more sustainable. Plus has received a number of industry awards and distinctions for its transformative technology and business momentum from
Fast Company,
Forbes,
Insider,
Consumer Electronics Show,
AUVSI, and others. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.
Responsibilities:Design and implement detection fusion and tracking algorithms to improve perception performance in real time and offline pseudo-label generation using a combination of camera, radar and lidar dataBenchmark and evaluate perception performance using quantitative metrics and testing methodologiesIdentify, troubleshoot, and resolve real-world perception issues encountered in autonomous driving scenariosEnsure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement effortsEnsure that technical work meets customer requirements, regulatory standards, and company quality policiesRequired Skills: Proficient in C/C++Experience with multi-modal detection fusion and tracking algorithmsStrong understanding of computer vision and perception systemsStrong understanding of sensing with cameras, radars and lidarsExcellent problem-solving skills and attention to detailPreferred Skills:Master's or Ph.D. in Computer Science, Electrical Engineering, Robotics, or related fieldExperience with perception systems in autonomous vehicles or roboticsHands-on experience deploying machine learning models into production environmentsProficiency in deep learning frameworks like TensorFlow or PyTorchExperience with real-time systems, parallel computing, and optimization techniquesStrong knowledge of data structures, algorithms, and software design patternsYour opportunities joining Plus
Work, learn and grow in a highly future-oriented, innovative and dynamic field.
Wide range of opportunities for personal and professional development.