Artificial Intelligence/Machine Learning Engineer

As an experienced AI professional with over 4 years of practical experience, you will be responsible for developing and training computer vision models for various tasks such as object detection, image classification, segmentation, OCR, face recognition, and anomaly detection. Your expertise will be utilized to optimize these models for performance on edge devices like NVIDIA Jetson, OpenVINO, and TensorRT. You will also be involved in processing and annotating image/video datasets, applying data augmentation techniques, and working with Large Language Models. Your strong understanding of statistical analysis and machine learning algorithms will be crucial in implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. Additionally, your knowledge of image processing concepts like thresholding, contour detection, and transformations will be applied to tasks like model optimization, quantization, and deploying to edge devices such as Jetson Nano/Xavier and Coral. Proficiency in Python (or C++) programming is required, along with expertise in OpenCV, NumPy, and PyTorch/TensorFlow. Hands-on experience with real-time computer vision applications and models like YOLOv5/v8, Mask R-CNN, and DeepSORT will be beneficial. You will collaborate with multiple teams, contribute to key decisions, and lead the implementation of large language models in AI applications. Researching and applying cutting-edge AI techniques to enhance system performance will be part of your responsibilities, as well as contributing to the development and deployment of AI solutions across various domains. In terms of requirements, you will design, develop, and deploy ML models for OCR-based text extraction, table and line-item detection in invoices/receipts/forms, and named entity recognition. Your role will involve evaluating and integrating third-party OCR tools, developing pre-processing/post-processing pipelines for image/text data, and working with video analytics platforms and MLOps tools. A background in academic CV research or published papers, knowledge of GPU acceleration, CUDA, and hardware integration will be advantageous for this position.,