Computer Vision Software Engineer

Continental

Budapest, Hungary

Your tasks

Our Data Enrichment team is, dedicated to improving the searchability and usability of image data for AI training and simulation. Our mission is to generate rich, descriptive metadata that captures the semantics of various road scenarios, providing invaluable insights for algorithm developers.

Responsibilities

Develop and implement computer vision algorithms to analyze and interpret images, generating accurate and comprehensive semantic metadata;
Design and maintain machine learning models for image recognition, object detection, and classification;
Conduct thorough testing and validation of computer vision systems to ensure reliability and accuracy;
Optimize and scale computer vision algorithms for real-time performance and deployment;
Stay up-to-date with the latest advancements in computer vision and machine learning technologies, incorporating best practices into the development process;
Analyze and process large datasets, ensuring data quality and consistency;
Contribute to the development of tools and pipelines to streamline the generation and management of semantic metadata.

Your profile

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mathematics, or a related field;
Proven experience in computer vision and image processing, with a strong portfolio of relevant projects;
Proficiency in Python and libraries such as OpenCV, TensorFlow, PyTorch, or similar frameworks;
Solid understanding of machine learning concepts and techniques, particularly in the context of computer vision;
Experience with deep learning architectures, such as convolutional neural networks (CNNs) and other relevant models;
Strong analytical and problem-solving skills, with the ability to work with complex and ambiguous datasets;
Familiarity with data annotation tools and techniques for generating high-quality training datasets;
Excellent communication and teamwork skills, with the ability to collaborate effectively with diverse teams;
Experience with cloud platforms (e.g., AWS, Google Cloud) and containerization (e.g., Docker) is a plus;
Strong organizational skills and the ability to manage multiple projects and priorities effectively.

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