Machine Learning and Computer Vision Engineer

Job description

Machine Learning and Computer Vision Engineer Company Overview: A leading innovator in automotive safety and advanced driver assistance systems (ADAS) is seeking a skilled Machine Learning and Computer Vision Engineer to join their development team. This company focuses on cutting-edge sensor technology, laser scanning, and AI-driven perception systems that improve urban traffic safety and reduce collisions with vulnerable road users. Role Overview: This role will be crucial to developing and refining perception algorithms and machine learning models that drive next-generation automotive systems. The ideal candidate will bring a blend of technical expertise in machine learning and computer vision, coupled with experience in managing large datasets for training and validation. Responsibilities: Develop and optimize machine learning models and algorithms for computer vision, focusing on real-time object detection and tracking. Use machine learning frameworks (e.g., TensorFlow, PyTorch) and computer vision libraries (e.g., OpenCV) to preprocess image and video data. Implement and improve auto-labeling and data annotation processes, using techniques like active learning or weak supervision to efficiently manage large-scale datasets. Collaborate with cross-functional teams to integrate perception models into complex ADAS and autonomous systems. Qualifications: Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field. Proven experience in machine learning and computer vision, particularly with model training, data preprocessing, and real-time applications. Proficiency with ML frameworks (TensorFlow, PyTorch) and vision libraries (OpenCV). Familiarity with auto-labeling tools, active learning, and weak supervision techniques. Strong analytical and problem-solving skills. Experience in the automotive industry is a plus, particularly in ADAS or autonomous driving.