Overview • Drive innovation in computer vision, developing cutting-edge solutions for autonomous systems and embedded technologies. • Collaborate with multidisciplinary teams to integrate advanced vision algorithms into hardware platforms seamlessly. • Optimize machine learning models for real-time applications, ensuring reliability and high performance. • Provide technical leadership and mentorship to engineers specializing in computer vision and machine learning. • Define and implement testing protocols to validate system performance under diverse conditions. • Support the transition from prototype development to production-grade systems with robust deployment strategies. • Stay abreast of emerging trends in computer vision and machine learning to maintain competitive expertise. • Contribute to groundbreaking advancements in autonomous systems technology. Key Responsibilities & Duties • Develop and implement advanced computer vision algorithms optimized for autonomous systems and embedded environments. • Collaborate with hardware engineers to integrate vision capabilities effectively into embedded platforms. • Optimize machine learning models for embedded environments, ensuring high reliability and performance. • Design and execute testing strategies to validate system robustness across operational conditions. • Mentor junior team members, fostering expertise in machine learning and computer vision methodologies. • Contribute to the development of production-grade systems, ensuring adaptability and compliance with rigorous standards. • Collaborate with interdisciplinary teams to address complex engineering challenges and advance autonomous technologies. • Stay updated on emerging trends in computer vision and machine learning to drive innovation. Job Requirements • Master’s degree or higher in Computer Science, Electrical Engineering, or related field with specialization in computer vision and machine learning. • Minimum of 9 years of experience in developing machine-learning-based computer vision systems, preferably for autonomous platforms. • Proficiency in programming languages such as Python and C++, with experience in ML frameworks like PyTorch or TensorFlow. • Extensive experience with embedded systems and integration of vision algorithms into hardware environments. • Familiarity with multi-sensor systems, including cameras, LiDAR, and radar technologies. • Proven ability to deploy real-time and safety-critical computer vision solutions in production settings. • Strong collaborative skills and a passion for mentoring and interdisciplinary problem-solving. • Commitment to driving innovation and advancing autonomous system capabilities.