Omkar Borhade
Machine Learning Engineer at Cimatron
Pune, Maharashtra, India
Summary
🤩
Rockstar🎓
Top SchoolOmkar Borhade is a Machine Learning Engineer based in Pune with four years of experience building AI-driven solutions for CAD/CAM and manufacturing domains. He has transitioned from mechanical engineering and simulation work into applied ML, contributing to feature recognition systems, energy management algorithms, and Cimatron API integrations. At Prescient/Cimatron he combined deep learning, LLMs, and autonomous agent ideas to bridge domain expertise with practical product enhancements. His open-source contribution to TensorFlow Datasets—adding identity features to the celeb_a dataset—highlights attention to dataset design and reproducible ML workflows. He brings hands-on experience across Python, C++, and C# and a background in GT‑Suite simulation and motor/battery sizing that gives him a rare systems-level view of AI for manufacturing. Colleagues describe him as a pragmatic engineer who turns deep domain knowledge into production-ready ML features.
4 years of coding experience
3 years of employment as a software developer
B.Tech, Mechanical Engineering, B.Tech, Mechanical Engineering at Vishwakarma Institute Of TechnologyScience, Grade A with distinction, Science, Grade A with distinction at Birla College of Arts Science & Commerce Birla College Road Kalyan Dist Thane 421 304
Marathi, Hindi, English, German, Sanskrit
Github Skills (9)
machine-learning10
tensorflow10
data-model10
user-data10
data-set10
datasets10
python9
numpy8
jax7
Programming languages (8)
Github contributions (5)
tensorflow/datasets
May 2023 - Jun 2023
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
Role in this project:
Data Scientist
Data ScientistContributions:2 reviews, 3 PRs, 10 comments in 16 days
Contributions summary:Omkar primarily contributed to the `celeb_a` dataset integration within the TensorFlow Datasets project. Their work involved adding an "identity" feature to the dataset, updating the builder to include identity data, and modifying test files to reflect these changes. The user also created dummy data for the identity feature. This indicates a focus on dataset manipulation and extending the existing data structure within the library.
datanumpydeep-learningdatasetmachine-learning
OmkarBorhade98/OmkarBorhade98
Oct 2022 - Jan 2024
Contributions:5 PRs, 7 pushes, 6 branches in 1 year 3 months
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