Kriti Kohli
About
Kriti Kohli is from New York City Metropolitan Area. Kriti is currently Senior Manager, GenAI at Google. In Kriti's previous role as a Engineering Leadership, Machine Learning at Netflix, Kriti worked in New York, New York until Jan 2026. Prior to joining Netflix, Kriti was a Head of Machine Learning, Core Magic and Optimize at Shopify and held the position of Head of Machine Learning, Core Magic and Optimize at New York, New York. Prior to that, Kriti was a Senior Manager, AI/ML Workflows at IBM, based in New York, New York from Jan 2019 to Aug 2021. Kriti started working as Data Science Manager at Applied Materials in Sunnyvale, California in May 2017. From Jul 2015 to May 2017, Kriti was Member of Technical Staff at GLOBALFOUNDRIES, based in New York, New York. Prior to that, Kriti was a Research Scientist at IBM Research, based in New York, New York from May 2012 to Jul 2015. Kriti started working as Postdoctoral Researcher at Penn State University in Jan 2009.
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Kriti Kohli's current jobs
GenAI in Workspace
Kriti Kohli's past jobs
Leading teams of Applied ML & GenAI Research and Engineering for - Reward Models in core recommender systems - LLM alignment and evaluation
Leading teams ranging from building LLMs and generative AI to marketing automations and Adtech attribution products that help merchants drive customer engagement for their business on Shopify. My teams built the products featured on shopify.com/magic including Sidekick Areas included: - LLM agents - Auto-Evals, LLM-as-a-judge - Adversarial agents
Leading multiple teams of data scientists and machine learning engineers to develop scalable solutions for - Expense Fraud Detection - AI-based Pricing algorithms for multi-hierarchical enterprises - NLP Entity Extraction and Competitive Insights generation - Intelligent workflow automation using OCR and NLP - Demand Sensing for Omnichannel Retail
Started up a team of data scientists responsible for delivering end-to-end machine learning applications to optimize supply chain and global operations We deployed a wide range of products such as - Customer segmentation models using unsupervised learning algorithms - Developing demand prediction and capacity forecasting deep learning models - Integrating Machine Learning directly in enterprise ERP, MRP tools
As a tech lead, I led a small team of scientists to develop and implement machine learning algorithms Key initiatives included - - Image classification models to identify defects in device images - Clustering algorithms for geometric pattern recognition - Automating code release documentation • Key skills: Python, Lua, Image classification, Computer Vision, Machine Learning, sklearn, opencv
Built computer vision models for economic prediction models using geospatial image datasets. • Key Skills: Python, Computer Vision, Machine Learning
Developed algorithms to determine the magnetic properties and physical line edge roughness from electron microscope images. • Key Skills: Python, MATLAB, Image Analysis