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Computer Vision Engineer
2 weeks ago
We are looking for a skilled and enthusiastic Computer Vision Engineer to join our team. As a Computer Vision Engineer, you will be responsible for developing and implementing computer vision algorithms and solutions to solve challenging visual recognition problems. Your expertise in image and video analysis will be essential in enhancing our products and services.
Job Responsibilities
- Algorithm Development: Design, implement, and optimize computer vision algorithms for image and video analysis tasks such as object detection, image segmentation, and image classification.
- Environment Setup: Set up and maintain computer vision development environments, using popular libraries and frameworks such as OpenCV, TensorFlow, or PyTorch.
- Data Preprocessing: Prepare and preprocess image and video datasets to ensure data quality and suitability for model training and validation.
- Model Training and Evaluation: Train and fine-tune computer vision models using deep learning frameworks. Evaluate model performance and optimize for accuracy and efficiency.
- Integration: Collaborate with software engineers to integrate computer vision models into production systems or real-time applications.
- Research and Innovation: Stay up-to-date with the latest advancements in computer vision research and explore new methodologies to improve our visual recognition capabilities.
- Documentation and Communication: Document your work thoroughly, including algorithms, methodologies, and results. Present findings and progress to the team and stakeholders in a clear and concise manner.
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
- Solid understanding of computer vision fundamentals and relevant algorithms.
- Proficiency in programming languages such as Python or C++.
- Experience with computer vision libraries like OpenCV and deep learning frameworks like TensorFlow or PyTorch.
- Familiarity with image and video data preprocessing techniques.
- Strong problem-solving skills and the ability to think creatively to tackle visual recognition challenges.
- Previous experience in developing and deploying computer vision applications or projects.
- Knowledge of GPU acceleration for deep learning training (e.g., CUDA).
- Familiarity with cloud-based platforms for computer vision development and deployment (e.g., AWS, GCP, Azure).
- Understanding of 3D computer vision and stereo vision techniques.
- Experience with object detection frameworks like YOLO or SSD.
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