About this role
Responsibilities:
Design and implement machine learning algorithms for object detection, tracking, and classification using camera data.
Develop and optimize computer vision algorithms for tasks such as lane detection, traffic sign recognition, and pedestrian detection.
Work closely with cross-functional teams to integrate machine learning models into existing systems.
Stay up-to-date on the latest advancements in machine learning and computer vision and apply them to real-world problems.
Analyze and improve the performance of existing machine learning models.
Contribute to the development of innovative camera vision solutions for advanced driver assistance systems (ADAS) and autonomous driving.
Design and build Visual Language Models
Qualifications:
Ph.D. in Computer Science, Machine Learning, or a related field.
Strong understanding of machine learning algorithms, including deep learning and convolutional neural networks.
Extensive experience in computer vision, image processing, and object recognition.
Proficiency in programming languages such as Python and C++.
Experience with deep learning frameworks such as TensorFlow or PyTorch.
Familiarity with automotive-grade standards and safety-critical applications is a plus.
Strong problem-solving and analytical skills.
Ability to work independently and as part of a team.