Bharathan Balaji
Senior Applied Scientist at Amazon
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolBharathan Balaji is a Senior Applied Scientist at Amazon in Seattle with nine years of experience and a PhD in Computer Engineering from UC San Diego. He develops ML-driven methods and systems that accelerate sustainability science, applying reinforcement learning, IoT, and smart-building technologies to reduce waste, improve education, and automate operations. He helped launch and scale AWS offerings like SageMaker RL and DeepRacer and contributes practical example notebooks to the widely used aws/amazon-sagemaker-examples repo to make advanced ML accessible to customers. A prolific researcher with 62 publications and over 3,000 citations, he combines academic rigor and cross-institution collaboration with hands-on product engineering to move ideas into production.
10 years of coding experience
University of California San DiegoUniversity of California, San DiegoBachelor of Technology, Electronics and Communication Engineering, Bachelor of Technology, Electronics and Communication Engineering at Visvesvaraya National Institute of TechnologyHigh School Certificate, Computer Science, High School Certificate, Computer Science at Atomic Energy Central School
Hindi, Tamil, English
Github Skills (12)
xgboost10
machine-learning10
jupyter-notebook10
aws10
sagemaker10
data-science9
deep-learning8
deep-learning-ai8
trainings7
reinforcement-learning7
python7
inference7
Programming languages (5)
Github contributions (5)
aws/amazon-sagemaker-examples
Apr 2019 - Nov 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:13 commits, 18 PRs, 1 branch in 7 months
Contributions summary:Bharathan primarily contributes to example notebooks for Amazon SageMaker, showcasing machine learning model development, training, and deployment. They have made changes related to hyperparameter tuning using XGBoost, and also made several revisions to the example notebooks, including fixes and corrections. The user's work is focused on demonstrating various machine learning techniques and providing practical examples within the SageMaker ecosystem.
pythonjupyter-notebooktrainingawssagemaker
amazon-science/carbon-assessment-with-ml
Feb 2023 - Mar 2025
CaML: Carbon Footprinting of Household Products with Zero-Shot Semantic Text Similarity
Contributions:12 PRs, 25 pushes, 5 comments in 2 years 1 month
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.