Headline

AI Engineer | Data Science Graduate | Building Scalable AI Systems for Real-World Impact

About

I'm a Data Science Graduate passionate about turning data into scalable AI products. Currently completing my MS in Data Science at Michigan Tech, I bring hands-on experience in deploying ML models for NLP, risk scoring, and financial document parsing in real-world systems. I've worked with startups and academic labs, where I’ve built LLM-powered summarization apps, Dockerized ML pipelines, and deployed inference APIs with FastAPI, AWS Lambda, and Kubernetes. I'm also the author of a peer-reviewed publication on gene biomarker discovery using deep learning. Now I’m actively seeking full-time roles where I can apply my skills in AI/ML, cloud deployment, and MLOps to build real-world impact—especially in fintech, healthcare, or AI product startups. 📬 Let’s connect if you're hiring for ML, MLOps, or AI Engineering roles!

Location

Pune District

AI stack

codex

opencode

Work experience

AI Engineer at Realfy Inc., Oct 2025 - May 2026 · 8 mos, Michigan, United States, Architected an AI platform enabling creator-specific and public information access with low end-to-end latency Implemented Retrieval Augmented Generation with indexed documents, increasing factual response accuracy by 45% Designed scalable backend APIs using FastAPI to support speech ingestion, retrieval, and generation Deployed GPU-hosted inference services with Docker and Kubernetes, maintaining 99.95% system availability Integrated secure identity workflows and role-based access to align with platform and public-system requirements

Research Assistant at Michigan Technological University, Aug 2023 - Oct 2025 · 2 yrs 3 mos, Houghton, MI, Built DyGAF, an attention-based model for biomarker ranking, achieving 94% classification accuracy Enhanced signal detection precision by 22% via TMM normalization and Random Forest selection Released Dockerized models with retraining triggers, reducing manual updates by 60% Detected model drift early using monitoring scripts, lowering downtime by 30% Managed preprocessing on NCBI datasets, including data-acquisition, and cleaning to prepare inputs for ML models Formulated and fine-tuned predictive models to analyze genetic interactions, achieving 93% accuracy

Software Engineering Intern at Fyle, Oct 2021 - Apr 2022 · 7 mos, Operated on data-extraction of information from digital and paper receipts using ML/AI to create expenses. Leveraged and deployed an innovative data extraction pipeline using Named Entity Recognition and NLP in Python, enabling high-efficiency data processing of digital and paper receipts. Enhanced real-time data processing performance by 30% through optimized algorithms in C++ and Python Collaborated and leveraged scalable AWS Textract for cloud-based document processing

Education

Master's degree, Data Science, Michigan Technological University

Bachelor's degree, Mechanical Engineering, Progressive Education Society's Modern College of Engineering

Public links

github: https://github.com/Himanshuwagh