Staff Computer Vision Engineer

Overview

• Develop and optimize computer vision algorithms for autonomous turret platforms, focusing on real-time drone detection, tracking, and classification.
• Design, build, and deploy machine learning models optimized for embedded environments with performance, reliability, and accuracy in mind.
• Collaborate with hardware engineers to integrate computer vision capabilities into system architecture.
• Define and execute testing strategies to ensure robust performance across diverse operational conditions.
• Provide technical leadership and mentorship to junior engineers, fostering expertise in machine learning and computer vision.
• Support the transition from prototype to military-grade systems, including development of variants for different platforms.
• Collaborate on interdisciplinary engineering challenges to advance autonomous systems technology.

Key Responsibilities & Duties

• Lead the development of computer vision algorithms for real-time applications in autonomous systems.
• Optimize machine learning models for embedded hardware environments, ensuring high performance and reliability.
• Integrate vision algorithms with hardware platforms, collaborating with electrical engineers.
• Develop and implement testing protocols for validation across operational conditions.
• Mentor junior engineers, providing guidance in machine learning and computer vision techniques.
• Contribute to the development of military-grade systems, ensuring robustness and adaptability.
• Collaborate with multi-disciplinary teams to address complex engineering challenges.

Job Requirements

• Master’s degree or higher in Computer Science, Electrical Engineering, or related field with a focus on machine learning and computer vision.
• Minimum of 9 years of experience developing machine-learning-based computer vision systems, preferably in robotics or autonomous systems.
• Proficiency in Python and C++, and experience with ML frameworks like PyTorch or TensorFlow.
• Experience with embedded systems and integration of vision algorithms into hardware platforms.
• Familiarity with multi-sensor systems such as cameras, LiDAR, and radar.
• Demonstrated ability to deploy real-time and safety-critical computer vision solutions in production environments.
• Strong collaborative skills and interest in mentoring and interdisciplinary problem-solving.