Omkar Mehta
Senior Software Engineer at NVIDIA
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolOmkar Mehta is a Senior Software Engineer with a decade of experience building production-grade data and ML pipelines across cloud platforms, currently at NVIDIA in Sunnyvale. He combines an MS in Industrial Engineering (Advanced Analytics) with hands-on expertise in AWS/GCP/Azure, PySpark/Databricks, and deploying GPU-accelerated data platforms and Spark workloads. Omkar has delivered cost-saving, production time-series and deep learning systems (including an LSTM-based predictor that saved ~$1M annually at BPCL) and has built large-scale streaming and ingestion pipelines for cloud gaming and enterprise analytics. Known for "rubber duck debugging," he focuses on data quality and end-to-end architecture that turns messy inputs into business impact, and he mentors teams in agile delivery. Quietly analytical, he pairs strong algorithmic skills (150+ LeetCode problems) with product-minded engineering—bridging research, teaching, and productionization.
10 years of coding experience
7 years of employment as a software developer
Bachelor’s degree, Chemical Engineering, 8.72/10, Bachelor’s degree, Chemical Engineering, 8.72/10 at Institute Of Chemical TechnologyMS in Industrial Engineering, Advanced Analytics, MS in Industrial Engineering, Advanced Analytics at University of Illinois Urbana-ChampaignHigh School, Higher Secondary Examination, 90.33%, High School, Higher Secondary Examination, 90.33% at Shikshan Prasarak Mandalis Sir Parshurambhau College Arts, Science & Commerce Tilak Road Pune 30
English, Marathi, Hindi
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (37)
oauth8
authentication8
jwt8
nodejs7
react7
auth7
stateless6
nuxt6
nextjs6
sveltekit5
javascript5
vscode4
csrf4
solidjs4
databricks-cli4
Programming languages (4)
Github contributions (5)
OmkarMehta/Classification-on-textual-data
Feb 2019 - Feb 2021
Main purpose of this project is to understand different methods of classifying textual data. I've used "20 newsgroup" dataset. It is a collection of approximately 20,000 newsgroup documents, partitioned (nearly) evenly across 20 different newsgroups, each corresponding to a different topic.
Contributions:12 PRs, 21 pushes, 6 branches in 2 years
newsgroupswikimediacorpus-linguisticscorpusdataset
OmkarMehta/SSFwithNODE
Jul 2021 - Nov 2021
Contributions:197 commits, 8 pushes in 3 months
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