Usama Yaseen is a Python developer and AI/ML engineer with 11 years of hands-on experience and a 5+ year focus on applied machine learning across industry and academia. Based in Lahore, he designs and deploys end-to-end AI solutions—from RAG pipelines and LLM fine-tuning to multi-agent architectures, voice agents, and low-latency real-time systems—frequently using LangChain, LangGraph, and cloud-native tooling on AWS/GCP. He has led and mentored teams as a Lead Data Scientist while shipping production ML systems for healthcare, fintech, and agriculture, including CNN-based medical imaging and YOLO object detection. As a prolific freelance engineer he collaborates directly with clients to turn domain requirements into scalable, containerized deployments with CI/CD and MLOps best practices. An active open-source contributor, he implemented NER augmentation and back-translation transformations in the well-known NL-Augmenter repository, highlighting a practical focus on robust NLP data augmentation. His strong academic foundation (BS CS, 3.86 GPA) complements a knack for bridging research ideas into production-ready AI products.
11 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Computer Science, CGPA : 3.86, Bachelor's degree, Computer Science, CGPA : 3.86 at University Of Central Punjab
NL-Augmenter 🦎 → 🐍 A Collaborative Repository of Natural Language Transformations
Role in this project:
ML Engineer
Contributions:14 reviews, 16 commits, 4 PRs in 2 months
Contributions summary:Usama contributed to the development of Named Entity Recognition (NER) augmentation techniques within the NL-Augmenter repository. Their work included the initial commit and implementation of an entity mention replacement transformation, along with the addition of keywords and test cases to the code. They also implemented a back-translation NER transformation using the FSMT model for German-to-English and English-to-German translations.
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