Pooja Ahuja
Machine Learning Engineer at ServiceNow
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolPooja Ahuja is a Machine Learning Engineer with 13 years of experience building production ML systems and research-driven models across startups and enterprise teams in the Bay Area. Currently working on LLM-driven search at ServiceNow and prior to that advancing natural language understanding at Glean, she blends applied research with pragmatic engineering to ship scalable search and recommendation features. Her background spans deep learning research at HPE Aruba, founding ML work on anomaly and log classification at JASK, and production recommender and automation systems at Chewy, where she introduced novel recommendation math and the company’s first ML-driven pricing pipelines. She contributes practical automation tooling on GitHub—like a Selenium-based delivery slot autobuyer—and frequently moves ideas from prototype to production. Comfortable in both distributed data stacks (PySpark, AWS) and model research, Pooja pairs academic rigor (MS thesis in ML) with a knack for inventive, impact-driven solutions. Colleagues describe her as a problem-solver who surfaces simple rules from complex gradients to make models more actionable.
12 years of coding experience
6 years of employment as a software developer
Master’s Degree with a Thesis Machine Learning, Master’s Degree with a Thesis Machine Learning at University of Nebraska-Lincoln
Marathi, Hindi, English
Github Skills (9)
automation10
automations10
selenium-ide10
beautifulsoup10
selenium10
python10
webscraping10
chrome9
firefox9
Programming languages (4)
Github contributions (5)
pcomputo/Whole-Foods-Delivery-Slot
Mar 2020 - May 2020
Automated script for Whole Foods and Amazon Fresh delivery slot
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:88 commits, 6 PRs, 82 pushes in 1 month
Contributions summary:Pooja primarily focused on developing an automated script for Whole Foods and Amazon Fresh delivery slot detection. Their work involved the use of Selenium with the Chrome and Firefox web drivers, BeautifulSoup for web scraping, and Python for implementing the core logic. They implemented features to monitor for delivery slots, with the addition of sound notifications, and also implemented autobuy functionalities.
whole-foodsscriptpythonamazon-freshamazon
pcomputo/webpage-classifier
Oct 2015 - Nov 2015
Contributions:27 commits, 26 pushes, 1 branch in 1 month
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