Udit Bhatia
Product Manager at Google
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolUdit Bhatia is a product leader with nine years of experience building B2B hardware and cloud products, currently shaping Cloud Network Security at Google from Seattle. He combines deep networking and systems expertise gained across multiple roles at Cisco with product strategy and go-to-market execution honed at Fiserv and Cisco’s Enterprise Switching team. Udit’s background as a hands-on consulting engineer informs his data-driven approach—he’s led automation initiatives that cut validation times by up to 60% and developed KPI-based product lifecycle strategies for large portfolios. He also bridges product and machine learning, contributing a reinforcement-learning training example to Amazon SageMaker that required custom container and environment work. An MBA from Carnegie Mellon Tepper complements his technical roots (B.Tech in Computer Engineering) and helps him translate complex technical trade-offs into commercial outcomes. Colleagues describe him as a pragmatic integrator who reduces product complexity while accelerating time-to-market.
8 years of coding experience
7 years of employment as a software developer
Bachelor of Technology (B.Tech.), Computer Engineering, Bachelor of Technology (B.Tech.), Computer Engineering at Vellore Institute of TechnologyMaster of Business Administration - MBA (Strategy,Marketing & Organizational Behavior), Master of Business Administration - MBA (Strategy,Marketing & Organizational Behavior) at Carnegie Mellon University - Tepper School of Business
English, Hindi, Spanish
Github Skills (10)
machine-learning10
jupyter-notebook10
aws10
python10
reinforcement-learning10
sagemaker10
dockers9
deeplearning-ai9
deep-learning9
docker9
Programming languages (2)
Github contributions (5)
aws/amazon-sagemaker-examples
Nov 2018 - Jan 2019
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Role in this project:
ML Engineer
ML EngineerContributions:6 commits, 1 PR, 17 comments in 1 month
Contributions summary:Udit contributed to the `aws/amazon-sagemaker-examples` repository by adding an example Jupyter notebook demonstrating training of a Roboschool HalfCheetah RL model using stable-baselines on Amazon SageMaker. This involved setting up the environment, building a custom Docker container with Roboschool and stable-baselines dependencies, and writing the training code within the notebook. The changes show the user's focus on integrating reinforcement learning algorithms and training environments with SageMaker.
pythonjupyter-notebooktrainingawssagemaker
uditbhatia/sagemaker-tensorflow-container
Dec 2018 - Jan 2019
This support code is used for making the TensorFlow framework run on Amazon SageMaker.
Contributions:13 pushes, 3 branches in 1 month
sagemakeramazon-sagemakertensorflow-frameworkdeep-learningamazon
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