Aditya Oke
Machine Learning Intern at Carnegie Mellon University
United States
Summary
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Rockstar🎓
Top SchoolAditya Oke is a Machine Learning Engineer and researcher with seven years of experience bridging production-scale engineering and AI-safety research, currently pursuing an MS in Computational Data Science at Carnegie Mellon and interning at Motional. He focuses on LLM safety, alignment, and robustness, contributing to coding agents and agent safety projects as a CMU graduate researcher and teaching assistant for CMU’s inaugural LLM Applications course. His background includes large-scale data engineering at JPMorgan Chase—architecting TB-scale Spark/Databricks pipelines—and applied deep learning for autonomous systems in computer vision. An active open-source contributor, he has improved core PyTorch/vision functionality (GIoU, bounding-box ops, JIT compatibility) and strengthened documentation for IceVision, reflecting a blend of low-level ML engineering and developer-facing communication. Comfortable across PyTorch, RL, computer vision, and cloud platforms (AWS/GCP), he seeks research scientist or ML engineer roles focused on secure frontier models and alignment. Notably, he pairs production reliability with formal safety research, making him adept at shipping robust ML systems that anticipate real-world failure modes.
7 years of coding experience
6 years of employment as a software developer
Bachelor of Technology - BTech, Computer Science and Engineering, Bachelor of Technology - BTech, Computer Science and Engineering at Vellore Institute of TechnologyMaster's degree, Computational Data Science, Master's degree, Computational Data Science at Carnegie Mellon University
Hindi, English
Stackoverflow
1reputation
0reached
0answers
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Github Skills (14)
unit-testing10
user-manual10
computer-vision10
pytorch10
tensor10
tensorflow10
learn-ruby-on-rails10
pytest10
basics10
python10
documentation10
compile9
jit9
object-detection5
Programming languages (9)
Github contributions (5)
pytorch/vision
Sep 2020 - Jan 2023
Datasets, Transforms and Models specific to Computer Vision
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:464 reviews, 65 commits, 65 PRs in 2 years 4 months
Contributions summary:Aditya made multiple contributions focused on enhancing the functionality and reliability of the `pytorch/vision` repository. They implemented and tested new features, including the addition of Generalized IoU (GIoU) and bounding box conversions, along with associated documentation and unit tests. The user also refactored and improved existing code related to bounding box operations and incorporated JIT (Just-In-Time) compilation compatibility, while simultaneously correcting documentation and various small bugs within the code. Their work demonstrates a focus on improving the functionality and the robustness of the library.
computer-visionmachine-learning
airctic/icevision
Jun 2020 - Aug 2020
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come
Role in this project:Technical Writer
Technical WriterContributions:31 commits, 50 PRs, 441 comments in 2 months
Contributions summary:Aditya primarily contributed to the documentation and tutorial aspects of the "icevision" repository. The user added a contributing guide, FAQ section, and updated the README file to include these resources. Moreover, the user also updated existing documentation such as tutorials which provide guides and insights on how to use the library.
computer-visionfastaipytorch-lightningobject-detectiondeep-learning
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