Staff Computer Vision Engineer Overview • Lead the development of cutting-edge computer vision technologies for autonomous systems and robotics applications. • Collaborate with multidisciplinary teams to integrate advanced machine learning algorithms into high-performance embedded systems. • Drive innovation by conducting research to advance real-time vision technologies and maintain industry leadership. • Mentor and guide engineering teams to foster technical excellence and professional growth. • Contribute to the design and optimization of scalable systems for robust performance in diverse applications. • Ensure the reliability and efficiency of algorithms through rigorous testing and validation processes. • Support the transition of innovative prototypes to production-grade systems for deployment. • Engage in cutting-edge research to enhance computer vision and robotics technologies. Staff Computer Vision Engineer Key Responsibilities & Duties • Develop and refine advanced computer vision algorithms for autonomous systems and robotics applications. • Design machine learning models optimized for real-time performance and resource efficiency. • Collaborate with hardware teams to ensure seamless integration of vision systems into embedded architectures. • Conduct rigorous testing to validate algorithm performance across diverse operational scenarios. • Mentor junior engineers, enhancing team capabilities and fostering innovation. • Support the transition of prototypes to production-grade systems with advanced applications. • Stay updated on advancements in computer vision and robotics to drive innovation. • Contribute to the development of scalable solutions for complex vision challenges. Staff Computer Vision Engineer Job Requirements • Master's degree in Electrical Engineering, Computer Science, or a related field with a focus on machine learning and computer vision. • Minimum of 7 years of experience in developing machine-learning-based computer vision solutions. • Proficiency in programming languages such as Python and C++, and frameworks like TensorFlow or PyTorch. • Experience with embedded systems and hardware integration of vision algorithms. • Knowledge of sensor technologies including cameras, LIDAR, and RADAR, and their application in autonomous systems. • Proven track record in deploying real-time computer vision systems in operational environments. • Strong leadership and mentoring skills to guide technical teams effectively. • Ability to lead research initiatives and contribute to innovative solutions in the field.