Open to opportunities

Umang Methi

@umangmethi1

Message

I’m a Senior AI/ML Engineer specializing in GenAI, NLP, and scalable MLOps for real-world impact.

United States

Message

What I'm looking for

I’m looking to build and deploy GenAI/NLP systems end-to-end—fine-tuning LLMs, delivering RAG at scale, and strengthening MLOps on cloud platforms to improve performance, reliability, and measurable business outcomes.

Highly accomplished Senior AI/ML Engineer with over 10 years of extensive experience building, deploying, and optimizing AI and machine learning models. I specialize in Generative AI, NLP, MLOps, and Deep Learning—bringing practical solutions across finance, healthcare, retail, and transportation.

I design scalable AI agents and LLM-based systems, including fine-tuning with PyTorch and deploying robust RAG pipelines. At Microsoft, I developed a Generative AI agent, built a Neo4j-powered enterprise RAG pipeline, and improved inference speeds by 20% using GPU-accelerated computing on Azure.

I’ve also driven measurable outcomes as a Senior Data Scientist at Nike, including a 15% reduction in inventory costs and a 20% increase in sales conversion through ML personalization and Rekognition-based recommendations. I enjoy leading implementations, mentoring teams, and advancing model performance through continuous research.

Experience

Work history, roles, and key accomplishments

Generative AI Engineer

Microsoft Corporation

Feb 2023 - Feb 2026 (3 years)

Designed and developed a scalable generative AI agent using LLMs and advanced NLP to improve decision-making. Fine-tuned LLMs with PyTorch and built a Neo4j-based RAG pipeline, improving inference speeds by 20% with Azure GPU-accelerated deployment.

Fine Tuned LLMs RAG Neo4j PyTorch Azure TensorRT GPU Acceleration Rasa

Senior Data Scientist (ML/NLP)

Nike, Inc

Feb 2020 - Jan 2023 (2 years 11 months)

Deployed ML models on AWS SageMaker to optimize Nike’s supply chain, reducing inventory costs by 15%. Built NLP and recommendation solutions with AWS services, improving sales conversion by 20%, product development cycles by 30%, and forecasting/inventory accuracy by 18%, while leading MLOps implementation using Step Functions and SageMaker Pipelines.

AWS Sagemaker MLOps AWS Step Functions TensorFlow PyTorch

ML/Data Engineer

Urbint

Nov 2017 - Feb 2020 (2 years 3 months)

Developed recommendation systems for e-commerce clients using collaborative filtering, matrix factorization, and content-based approaches. Built deep learning medical imaging pipelines (YOLOv3, Faster R-CNN), deployed NLP sentiment analysis for social media monitoring, and applied time-series forecasting for environmental monitoring.

Recommendation Systems Collaborative Filtering Content Based Filtering YOLOv3 OpenCV Time Series Medical Imaging

Machine Learning Intern

Amazon

May 2017 - Oct 2017 (5 months)

Contributed to Amazon Alexa development by working on NLP/NLU and speech recognition to enhance voice-interaction capabilities. Assisted with integrating personalized recommendation models and helped optimize the Alexa voice recognition algorithms to improve accuracy and response time.

NLP NLU Speech Recognition TensorFlow Keras Recommendation Systems

Full Stack Developer

ActivTrak

Jun 2016 - Apr 2017 (10 months)

Developed scalable, responsive web applications by integrating front-end and back-end components across devices. Designed database models and server-side logic to support high-volume traffic and improve application stability and load performance.

React TypeScript JavaScript MongoDB Docker UI UX Design Performance Optimization