Kalyan R
AI Resident at Google
Hyderabad, Sindh, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolKalyan R is an AI researcher and engineer with nine years of experience, currently an AI Resident at Google working on machine learning for chemical synthesis at X. He holds a PhD in Machine Learning from the University of Oxford and has a track record of research and applied work across startups and industry, including generative-accelerated molecular simulation at Angstrom AI and context-aware view synthesis at Adobe. A proven backend developer and QA contributor in major open-source projects, he is an Apache Airflow committer and has contributed CUDA/system-introspection enhancements to Numba, reflecting deep familiarity with performance-sensitive ML tooling. Kalyan combines rigorous academic training with practical engineering—building large synthetic datasets and performant models—and often bridges research prototypes to production-ready systems. Based in Hyderabad and UK-affiliated, he brings a rare mix of compiler-level contributions, workflow engineering, and applied generative modeling to multidisciplinary ML problems.
9 years of coding experience
Indian Institute of Technology MadrasDoctor of Philosophy - PhD Machine Learning, Doctor of Philosophy - PhD Machine Learning at University of OxfordHigh School, High School at National Public School
Stackoverflow
4,892reputation
689kreached
125answers
59questions
python
top-5%
Github Skills (26)
pytest10
python10
llvm10
testing10
workflow-engine10
numpy10
compiler-compiler10
airflow10
cuda10
compiler10
numba10
data-engineering9
parallel9
typehinting9
type-checking9
Programming languages (14)
Github contributions (5)
apache/airflow
Jan 2023 - Apr 2025
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Back-end Developer & QA Engineer
Back-end Developer & QA EngineerContributions:313 reviews, 203 PRs, 1 push in 2 years 2 months
Contributions summary:Kalyan primarily focused on enhancing the robustness of the codebase by adding tests and improving type safety. Their work included refactoring code to use type hints and implementing comprehensive unit tests, particularly within the `airflow/models/baseoperator.py` and `airflow/models/dagbag.py` files. Furthermore, the user addressed a bug in the S3 hook, removing an unnecessary info log.
monitorpythonschedulerapacheprogrammatically
numba/numba
Mar 2021 - May 2021
NumPy aware dynamic Python compiler using LLVM
Role in this project:Back-end Developer
Back-end DeveloperContributions:3 reviews, 20 commits, 13 PRs in 2 months
Contributions summary:Kalyan focused on enhancing the Numba compiler by adding features related to CUDA device information and system introspection. They added and modified code to report CUDA runtime version, watchdog status, compute mode, and performance ratios. The contributions involved modifying existing files to include new system information and correcting for linting errors. The user's work also included merging branches and updating documentation.
cudapythonparallelnumpynumba
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