# Nagul Ulaganathan > Machine Learning Engineer Location: San Francisco, California, United States Profile: https://flows.cv/nagul Experienced Machine Learning and Software Engineer with a Master’s degree in Computer Science from University of Pennsylvania. With extensive experience in developing and deploying advanced AI solutions, I specialize in Generative AI, Computer Vision, NLP, Full-Stack development and data-driven strategies to solve complex challenges across industries. Proficient in designing scalable systems, optimizing machine learning workflows, and integrating innovative technologies to drive impactful outcomes. Passionate about bridging the gap between cutting-edge research and real-world applications, with a track record of delivering measurable results through technical expertise and collaborative problem-solving. ## Work Experience ### Machine Learning Engineer (Full Stack) @ Numentica Jan 2024 – Present | San Francisco, California, United States • Developed and deployed Generative AI applications using Custom fine-tuned Phi-3 multimodal models and Azure OpenAI LLMs, integrating computer vision techniques and meta-prompt engineering to significantly improve transcript text extraction accuracy and efficiency. • Implemented Retrieval-Augmented Generation (RAG) frameworks to combine LLM capabilities with external knowledge retrieval, enhancing the precision of text extraction from large-scale transcripts. • Designed and optimized robust data pipelines for processing and analyzing high-volume data, leveraging state-of-the-art machine learning models and cloud-based AI solutions to ensure scalability and performance. • Architected and built the entire backend stack to streamline and automate workflows, reducing processing latency and enhancing accuracy through seamless integration of multimodal AI, machine learning models, and advanced CV techniques. ### Software Engineer - ML @ Mavis Tire Jan 2023 – Jan 2024 | New York, New York, United States • Designed and developed scalable, high-performance applications supporting critical business processes for a retail platform with 1,500+ stores across the U.S., significantly improving system reliability and scalability. • Optimized transaction workflows by developing efficient APIs, resulting in a 70% reduction in transaction costs and enhancing system responsiveness. • Built a transfer management system using TypeScript and React to streamline and automate transfer tracking, enhancing operational accuracy and productivity. • Implemented dynamic, machine learning-driven pricing models, leading to a 15% revenue increase in targeted stores through optimized pricing strategies. • Developed and deployed computational models to forecast inventory demand, achieving a 30% reduction in excess inventory and improving overall supply chain efficiency. ### Machine Learning Engineer @ Standard AI Jan 2022 – Jan 2022 | San Francisco Bay Area • Leveraged HRNet to deploy a pose detection model for soft labeling, propelling pose detection performance by 4%. • Developed new evaluation methodologies and metrics for human feature extraction and autonomous pose predictions in retail stores to reduce labeling costs by identifying production failures. • Designed and created a workflow using optical flow to identify false positives and negatives in the pose model predictions. • Stabilized model pipeline by reducing jitter from model outputs through filtering techniques. ### Machine Learning Intern @ Redleaf Technologies Private Limited Jan 2020 – Jan 2020 | Coimbatore, Tamil Nadu, India • Developed models using techniques like object detection and semantic segmentation for identifying and segmenting objects from street view images to aid in grid layout planning. • Achieved 94% accuracy with a novel architecture of deep convolution neural networks for the classification of Satellite images and Grid maps which increased the product performance by 18% in terms of classification. • Improved model performance by 8% using transfer learning with various CNN models for Satellite image classification. ### Machine Learning Intern @ Numentica LLC Jan 2020 – Jan 2020 | Bengaluru, Karnataka, India • Amplified decision support by working on data cleaning, analysis, prediction and classification of data using machine learning models like Regression, Decision trees, K-NN, Random Forest, XGBoost, K-means and Neural Networks. • Collaborated with senior engineers for the deployment of ML models along with multiple features for data visualization. ### Software Engineer @ Amtex Systems Inc. Jan 2019 – Jan 2019 | Chennai, Tamil Nadu, India • Built the back-end for a web page to handle product purchases and reduced manual debugging effort by 70% by automating test scripts using Node.js, Python and other testing frameworks like Chai.js and Chakram. • Collaborated with a team of 10+ members to build APIs that handle authorizations between multiple pages. ## Education ### Master of Science - MSE in Computer and Information Sciences University of Pennsylvania ### Bachelor of Technology - BTech in Computer Science Vellore Institute of Technology ## Contact & Social - LinkedIn: https://linkedin.com/in/nagulu --- Source: https://flows.cv/nagul JSON Resume: https://flows.cv/nagul/resume.json Last updated: 2026-03-29