Kirat Mokha

About Kirat Mokha

I’m a Machine Learning Engineer with a Master’s degree in Machine Learning, specializing in deploying ML models to edge environments and building the data platforms that power large scale analytics. My work spans embedded model development, end-to-end data engineering, and MLOps using tools like Databricks, Delta Lake, Python, and Azure DevOps.I enjoy solving complex, cross-disciplinary problems and creating systems that make high quality data accessible, reliable, and actionable. I’ve led initiatives that standardize data pipelines, accelerate model development, and enable real time insights across engineering teams.I’m passionate about applying machine learning in real products, scaling data infrastructure, and driving organizations toward a truly data-driven future.

Experience

1. Machine Learning Engineer Ii

   Milwaukee Tool

   Nov 2024 — Present · Brookfield, WI, US

   As a Machine Learning Engineer on Milwaukee Tool’s Team (Analytics, Algorithms, and AI Applications); I focus on deploying machine learning models onto edge devices and building the data infrastructure that enables scalable, intelligent, and data driven product development. My work bridges embedded ML, cloud analytics, and end-to-end data engineering.Key Contributions- Designed and implemented embedded ML models for real time inference, feature extraction, and predictive analytics on constrained compute systems- Built end to end data pipelines that standardize high resolution tool data collection, processing, and modeling workflows across the organization- Developed scalable analytics and MLOps processes using Databricks, Delta Lake, Python, and Azure DevOps to automate data engineering, model retraining, CI/CD, and validation- Created dashboards and analysis tools that enable engineering teams to evaluate performance, accelerate experimentation, and make data driven decisions.Leadership- Selected for Milwaukee Tool’s Emerging Leaders Program with experience mentoring interns and collaborating across Embedded, IT, Security and Data teams- Contributed to long term strategy for ML adoption, data standardization, and the growth of the company’s data ecosystem.