Machine Learning Ai Engineer

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SREEHARI SREENATH

Charlottesville, VA ***** 304-***-**** ****.********@*****.***

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Seasoned AI engineer with 8+ years of professional experience working on AI/ ML training, LLM training efficiency, and Distributed Supercomputing (HPC). Master's degree in information systems with a 4.0 GPA with research published in the field of Machine Learning, Artificial Intelligence, and UAVs. Experience in Distributed Computing / High Performance Computing (HPC) Have performed hardware testing and validations on new cutting edge hardwares used for AI (GPUs, communication devices etc).

Work History

Senior AI Engineer - (contract)

Microsoft Research January 2024 - Current

● Collaborate on high-priority AI training projects within Microsoft's Scale-Out Readiness initiatives, optimizing AI/LLM models for GPU clusters to achieve faster training, earlier results, and resource efficiency.Preparing to share the framework at NVIDIA GTC 2025

● Achieved 230% speed-up for Physics of AGI team by optimizing Small Language Models (SLM) like the Phi series (used in Microsoft Copilot) using asynchronous functions, optimized GPU kernels, and improved network topologies

● Enabled 180% speed-up for AI4Science team's Mixture of Experts (MoE) models by optimizing pipeline and tensor parallelism, significantly reducing inefficiencies and lesser bubbles in the training pipeline

● Conducted comprehensive testing of new/pre-release GPUs, delivering constructive performance feedback to hardware partners.Provided detailed internal performance insights to Azure HPC, influencing hardware procurement decisions

Data Scientist - contract

Caterpillar January 2023 - December 2023

● Led condition monitoring projects to predict the end-of-life for CAT machines, driving aftermarket sales and reducing operational downtimes

● Proposed a new framework using a bi-directional LSTM model, replacing the previous physics-based model that achieved only 70% precision

● This led to a 24% increase in precision, raising it to 94%, and a 17% increase in recall

● Influenced over $200M+ in aftermarket sales by implementing predictive maintenance strategies and integrating machine learning insights into production systems

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Sr. Research Engineer / Sr. Machine learning Engineer Microsoft Research April 2021 - October 2022

● Partnered with Microsoft's Artificial Intelligence + Research team to optimize large-scale AI/ML models such as ResNet, Transformers (GPT, BERT), GANs, and RL algorithms (e.g., Twin-Delayed DDPG)

● Initiated and led the AI Supercomputer Efficiency Project, delivering over $1M in cost savings during the proof-of-concept stage and potential for $100M+ in annual savings

● Fine-tuned large distributed workloads on GPU clusters, leveraging tools like PyTorch, TensorFlow, Azure ML, Docker, and Kubernetes to maximize performance Lead Data Scientist (contract + freelance)

Extraslice October 2020 - Current

● Spearheaded development of an AI-powered real estate marketplace, revolutionizing landlord-tenant engagement and reducing processing times by 6x

● Collaborated with real estate consultants and SMEs to design a disruptive platform combining AI insights and business acumen

● Directed offshore and onshore teams to ensure high-quality product delivery and feature integration

● Built a property price estimation model akin to Zestimate, enhancing market pricing strategies Data Scientist (Research Assistant, part-time)

Marshall University August 2018 - September 2020

● Delivered data-driven Machine Learning solutions and statistical models/dashboards to clients such as ERDC (US Army Engineer Research and Development Center) and DEP (Dept. Of Environmental Protection)

● Developed and deployed time series anomaly detection models based on LSTM (Long Short-Term Memory) and SARIMA (Seasonal Auto-Regressive Integrated Moving Average) and other regression/classification models on IoT sensor data coming from major dams in the United States Graduate Teaching Assistant

Marshall University August 2019 - January 2020

● Gave lectures on special topics in Machine Learning for 56 students learning their first programming language (Python) in their undergraduate program and provided invaluable guidance on their undergraduate research projects as a mentor.

Data Scientist (internship)

Microexcel Inc., New Jersey, USA May 2018 - July 2018

● Improved cost estimation and project scheduling efficiency (by 19%) using machine learning algorithms

● Automated Tableau dashboards for ongoing projects and employee performances

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Machine Learning Engineer

Exacore IT solutions, India, India December 2015 - January 2018

● Delivered data-driven solutions to clients for their business problems

● Optimized more than 25% supply chain cost (Eastern spices) across south India

● Implemented AI powered patient health charts and recommendations, resulting in 12-20% more physician availability across various clinic facilities in BCMCH hospitals (India) Education

Master of Science in Information Systems

Marshall University, USA

GPA: 4.0

Bachelor of Technology in Mechanical Engineering

Amrita University, Coimbatore, India

Websites, Portfolios, Profiles

● https://www.linkedin.com/in/sreehari-sreenath/

● https://github.com/IamNirmata

Publications

● Assessment and Use of Unmanned Aerial Vehicle for Civil Structural Health Monitoring, The 3rd International Conference on Emerging Data and Industry 4.0 (EDI40-2020), https://doi.org/10.1016/j.procs.2020.03.174

● What People Complain about Drone Apps? A Large-Scale Empirical Study of Google Play Store Reviews, 11th International Conference on Ambient Systems, Networks and Technologies

(ANT-2020), https://doi.org/10.1016/j.procs.2020.03.124

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