Staff Computer Vision Engineer

Overview

• Lead the development and optimization of computer vision algorithms for autonomous systems, focusing on real-time drone detection, tracking, and classification.
• Design and implement machine learning models for resource-constrained environments ensuring high accuracy and reliability in operations.
• Collaborate with electrical engineers to integrate computer vision systems into hardware architectures for enhanced functionality.
• Conduct rigorous testing and validation of algorithms under diverse environmental conditions to ensure robustness and performance.
• Mentor junior engineers, fostering growth in machine learning and computer vision expertise within the organization.
• Contribute to the development of military-grade systems and variants for different weapon systems and engagement ranges.
• Work on cutting-edge technologies in robotics and autonomous systems, driving innovation and excellence.

Key Responsibilities & Duties

• Develop and optimize computer vision algorithms for real-time applications in autonomous systems.
• Design machine learning models suitable for resource-constrained environments ensuring operational reliability.
• Collaborate with hardware teams to integrate vision systems into electrical architectures effectively.
• Perform extensive testing and validation to ensure algorithm robustness across diverse scenarios.
• Mentor and guide junior engineers, fostering technical growth and team collaboration.
• Assist in transitioning prototypes to military-grade systems and developing system variants.
• Engage in continuous learning and application of advanced computer vision and robotics technologies.

Job Requirements

• Master's degree in Electrical Engineering, Computer Science, or related field with a focus on machine learning and computer vision.
• Minimum of 7 years of experience in machine-learning-based computer vision, preferably in robotics or safety-critical applications.
• Proficiency in Python and C++, and familiarity with frameworks like TensorFlow or PyTorch.
• Experience with embedded systems and hardware integration of computer vision algorithms.
• Knowledge of sensors such as cameras, LIDAR, and RADAR, and their integration into autonomous systems.
• Strong track record of developing and deploying real-time computer vision systems.
• Passion for robotics, machine learning, and computer vision, with a collaborative and mentoring mindset.