Computer Vision Engineer

• Develop real-time computer vision models for item recognition and object detection use cases

• Build and optimize AI models for item identification, classification, and localization within environments

• Design systems for 2D floor mapping and 3D planogram-based item positioning and tracking

• Work on end-to-end item recognition pipelines including data collection, labeling, training, and deployment

• Develop and maintain MLOps pipelines including model training, version control, and deployment workflows

• Create and manage scalable data pipelines for large-scale image and video datasets

• Implement labeling pipelines to ensure high-quality annotated datasets for model training

• Train and fine-tune deep learning models using frameworks like PyTorch and TensorFlow

• Work with NVIDIA-based technologies to optimize model performance and inference speed

• Collaborate with cross-functional teams to integrate computer vision solutions into production systems

• Continuously improve model accuracy, performance, and scalability for real-world applications

• Ensure robust model monitoring, retraining strategies, and lifecycle management