Computer Vision Engineer (Model Training)

As a talented and passionate Computer Vision Engineer with over 3 years of experience, you will join a growing AI team and be responsible for developing, training, fine-tuning, and optimizing computer vision models for real-world applications. Collaborating closely with AI researchers, data scientists, ML engineers, and product teams, you will build scalable solutions that deliver measurable business impact. - Design, develop, train, and deploy Computer Vision and Deep Learning models for image and video-based applications. - Build and optimize AI pipelines for data preprocessing, augmentation, annotation, training, validation, and inference. - Train and fine-tune models using frameworks such as PyTorch, TensorFlow, Keras, or OpenCV. - Develop solutions for object detection, image classification, semantic segmentation, OCR, facial recognition, tracking, and video analytics. - Evaluate model performance using appropriate metrics and continuously improve accuracy, precision, recall, and inference speed. - Work with large-scale image and video datasets, ensuring high-quality data preparation and labeling standards. - Implement transfer learning, model compression, quantization, and optimization techniques for production deployment. - Collaborate with MLOps and engineering teams to deploy models into production environments. - Research and implement the latest advancements in Computer Vision, Deep Learning, and Generative AI. - Conduct model testing, debugging, and performance benchmarking. - Document experiments, model architectures, training methodologies, and deployment processes. - Participate in technical discussions, code reviews, and architecture planning sessions. - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field. - 3+ years of hands-on experience in Computer Vision and AI Model Training. - Strong experience with Python and Computer Vision libraries such as OpenCV, Pillow, Scikit-Image, and NumPy. - Proficiency in Deep Learning frameworks including PyTorch, TensorFlow, or Keras. - Experience training and fine-tuning CNNs, Vision Transformers (ViTs), YOLO, Faster R-CNN, Mask R-CNN, SSD, or similar architectures. - Knowledge of image processing, feature extraction, object detection, segmentation, tracking, and OCR techniques. - Experience with data annotation tools and dataset management workflows. - Understanding of model evaluation, hyperparameter tuning, and experiment tracking. - Familiarity with cloud platforms such as AWS, Azure, or GCP. - Experience with Docker, Git, and ML deployment workflows. - Strong analytical, problem-solving, and debugging skills. - Excellent communication and collaboration abilities. (Note: Preferred qualifications and any additional details of the company are omitted from the provided Job Description) As a talented and passionate Computer Vision Engineer with over 3 years of experience, you will join a growing AI team and be responsible for developing, training, fine-tuning, and optimizing computer vision models for real-world applications. Collaborating closely with AI researchers, data scientists, ML engineers, and product teams, you will build scalable solutions that deliver measurable business impact. - Design, develop, train, and deploy Computer Vision and Deep Learning models for image and video-based applications. - Build and optimize AI pipelines for data preprocessing, augmentation, annotation, training, validation, and inference. - Train and fine-tune models using frameworks such as PyTorch, TensorFlow, Keras, or OpenCV. - Develop solutions for object detection, image classification, semantic segmentation, OCR, facial recognition, tracking, and video analytics. - Evaluate model performance using appropriate metrics and continuously improve accuracy, precision, recall, and inference speed. - Work with large-scale image and video datasets, ensuring high-quality data preparation and labeling standards. - Implement transfer learning, model compression, quantization, and optimization techniques for production deployment. - Collaborate with MLOps and engineering teams to deploy models into production environments. - Research and implement the latest advancements in Computer Vision, Deep Learning, and Generative AI. - Conduct model testing, debugging, and performance benchmarking. - Document experiments, model architectures, training methodologies, and deployment processes. - Participate in technical discussions, code reviews, and architecture planning sessions. - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field. - 3+ years of hands-on experience in Computer Vision and AI Model Training. - Strong experience with Python and Computer Vision libraries such as OpenCV, Pillow, Scikit-Image, and NumPy. - Proficiency in Deep Learning frameworks including PyTorch, TensorFlow, or Keras. - Experience training and fine-tu