Nima Eshraghi
Senior Machine Learning Engineer @Walmart Global Tech
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WORK HISTORY
Senior Machine Learning Engineer @Walmart Global Tech
Toronto, ON, CA
Computer Vision:• Automated end-to-end pipeline for 3D asset creation, enabling augmented reality feature for 70k+ assets.• Trained and tuned state-of-the-art deep learning models (GANs, Diffusion Models, CNNs) for a variety of tasks including image generation, object detection, segmentation, and quality analysis.• Directed a research group and served as a technical lead on diffusion models and multi-modal solutions, targeting personalized image generation- Natural Language Processing (NLP):• Optimized LLMs and multi-modal models, 26% Improved inference latency by algorithmic model optimization methods and frameworks (quantization, pruning, ONNX, TensorRT), while keeping performance metrics competitive.• Drove parameter-efficient fine-tuning techniques (LoRA, QLoRA) to enhance LLMs and Transformers performance for content summary and extracting information at scale.• Designed multi-modal Retrieval Augmented Generation (RAG) to learn over multiple modalities, and run similarity search with accelerated search mechanisms.
EDUCATION
University of Tehran
Master of Applies Science (MSc.)
Iran University of Science and Technology
Bachelor of Applied Science (B.A.Sc.)
University of Toronto
Doctor of Philosophy - PhD
ABOUT NIMA ESHRAGHI
8 years of experience in deep learning- Deep Learning: Designed and automated end-to-end pipelines, deployed in production, CI/CD.Training, Tuning and designing architectural improvements for a variety of deep learning models: GANs, Diffusion Models, Transformers, Large Language Models (LLMs), Multi-Modals, 3D GANs, Neural Fields (NeRFs), CNNs, BERTExperience with a diverse set of ML applications including 3D reconstruction, image generation, object detection and segmentation, text content summary, question-answering, information extraction, quality analysis, multi-modal learning Optimizing deep learning models, accelerated inference using frameworks and tools such as ONNX, TenorRT, etc- Optimization: Convex opt, Stochastic opt, Online opt, Mixed-Integer Programming, Multi-agent and Distributed opt- Networks: Computer & Communication Networks, Edge and Cloud Computing- Software Expertise: Python, PyTorch, Tensorflow, Keras, SQL, JAX, OpenCV, Scikit-learn, NLTK, Pandas, XGBoost, Git, Docker, C++, MATLAB, GCP, Azure, AWS, Spark
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