Computer Vision Engineer (Model Training)

Remote (Work From Anywhere) Experience: 3+ Years About the Role We are looking for a talented and passionate Computer Vision Engineer with hands-on experience in AI model training and deep learning to join our growing AI team. In this role, you will be responsible for developing, training, fine-tuning, and optimizing computer vision models for real-world applications such as object detection, image classification, segmentation, OCR, video analytics, and visual inspection systems. You will collaborate closely with AI researchers, data scientists, ML engineers, and product teams to build scalable computer vision solutions that deliver measurable business impact.

Key Responsibilities 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 and ensure 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.

Required Skills & Qualifications 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. Preferred Qualifications Experience with Multimodal AI, Vision-Language Models (VLMs), or Generative AI applications.

Knowledge of MLOps tools such as MLflow, Weights & Biases, Kubeflow, or Airflow. Experience with edge AI deployment using TensorRT, ONNX, NVIDIA Jetson, or OpenVINO. Familiarity with OCR frameworks such as EasyOCR, PaddleOCR, or Tesseract.

Experience working with large-scale video analytics systems. Contributions to open-source AI or Computer Vision projects.