Sanjana Reddy is a Senior Machine Learning Engineer at Google Cloud with seven years of experience building production ML and NLP systems across tech and enterprise products. She has a strong track record in end-to-end NLP—intent classification, entity extraction, coreference resolution and QA—from roles at SAP and LinkedIn to shipping ML labs and explainable-AI demos at Google. Her open-source contributions include adding a BERT-based text-classification lab and integrated gradients XAI examples to widely used Google Cloud training repos, reflecting a focus on practical developer education and model interpretability. Based in California and holding a CS master’s from USC, she blends research-informed prototyping with production deployment on Google Cloud AI Platform. Notably, she bridges product and engineering by turning data-driven insights into features that improve search and conversational experiences.
7 years of coding experience
2 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at University of Southern California
Bachelor's degree, Computer Science and Engineering, Bachelor's degree, Computer Science and Engineering at PES University
This repos contains notebooks for the Advanced Solutions Lab: ML Immersion
Role in this project:
ML Engineer
Contributions:263 reviews, 134 commits, 136 PRs in 1 year 5 months
Contributions summary:Sanjana implemented and documented explainable AI (XAI) techniques, specifically integrated gradients, within the context of an image classification project. The commits show the addition of code to create, train, and deploy models to Google Cloud AI Platform. The user also addressed feedback and added todo items to lab notebooks.
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
Role in this project:
ML Engineer
Contributions:9 reviews, 13 commits, 12 PRs in 2 months
Contributions summary:Sanjana added a new lab to the repository focused on text classification using BERT, indicating a focus on machine learning. The commits involved code changes related to fine-tuning BERT on a dataset of movie reviews, including loading models from TensorFlow Hub, building a model with a classifier, and training the model. The changes also include preprocessing text into an appropriate format.
gcpgoogle-cloud-platformgoogle-cloudtraining
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