Nilansh Rajput
Lead Data Scientist
Anandpur Sahib, Punjab, India
Summary
🤩
Rockstar🎓
Top SchoolNilansh Rajput is a Staff Data Scientist specializing in agentic and generative AI, with eight years of hands-on experience building production ML systems and conversational agents at Tide. An IIT Ropar graduate, he has led development of RAG-powered chatbots, semi-supervised labeling pipelines for low-label credit models, and an MLOps architecture that bridges experimentation to reliable production using Databricks, MLflow, Tecton and Snowflake. He also drove feature-store optimizations, model and feature monitoring, and eligibility engines that materially increased credit revenue and product availability. Beyond product work, Nilansh contributes to privacy-preserving NLP through OpenMined (notably improving PySyft serialization and Grid client security), reflecting a rare blend of applied NLP, privacy engineering, and operational rigour. He is based in Anandpur Sahib, Punjab, and is known for pragmatic trade-offs between reproducibility and rapid experimentation when shipping dependable AI systems.
7 years of coding experience
4 years of employment as a software developer
Bachelor of Technology Computer Science, Bachelor of Technology Computer Science at Indian Institute of Technology, Ropar
Github Skills (11)
json10
deserialization10
serializable10
serializer10
python10
serialization10
federated-learning9
testing8
cryptography8
boto6
aws6
Programming languages (4)
Github contributions (5)
OpenMined/PySyft
Jul 2020 - Oct 2022
Perform data science on data that remains in someone else's server
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 reviews, 8 commits, 6 PRs in 2 years 2 months
Contributions summary:Nilansh primarily focused on improving serialization and deserialization processes within the `pysyft` codebase, specifically for Grid client components. They addressed security concerns by migrating from pickle to JSON serialization, implemented and tested client serialization, and made adjustments to data-centric and model-centric FL client classes. Additionally, the user contributed to infrastructure by adding boto3 in the setup.py file and made changes to the CLI and AWS provider settings. Furthermore, they added a "get_copy" argument to get methods for objects.
pytorchcryptographyacquiringpythonscience
Nilanshrajput/PySyft
Mar 2020 - Oct 2022
A library for encrypted, privacy preserving machine learning
Contributions:29 pushes, 7 branches in 2 years 7 months
pythonprivacyprivacy-preserving-machine-learningmachine-learningencrypted
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