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AI Engineer with 2+ years in Federated Learning, LLM Fine-Tuning & RAG
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AI/ML Engineer with research and production experience in federated learning, LLM fine-tuning, and retrieval-augmented generation (RAG). Published 3 papers on federated learning and reinforcement learning. Hands-on with PyTorch, Hugging Face Transformers, Flower FL, and OpenFL, with a strong software engineering foundation in Python, C#, ASP.NET Core, and PostgreSQL for deploying ML systems at scale in healthcare SaaS.
Pune Institute of Computer Technology (PICT), Pune
B.E. Computer Engineering · Computer Engineering
August 1, 2020 – June 30, 2024
Simplify Healthcare
Associate Software Engineer – AI/ML Integration
October 1, 2024 – Present
Pune, Maharashtra, India
Savitribai Phule Pune University
Machine Learning Research Assistant (Part-Time)
February 1, 2024 – Present
India
Veritas LLC
AI/ML Intern
June 1, 2023 – June 1, 2024
India
Web Scraping AI Agent
June 29, 2026 – Present
Built a Streamlit-based intelligent extraction tool using OpenAI API function calling and Scrapy, enabling structured data extraction from arbitrary websites with natural language prompts and export to CSV/JSON.
Fine-Tuning LLMs using Federated Learning
NCACSI (National Conference on Advances in CSI)
June 30, 2026 – Present
Stock Trading using Reinforcement Learning
IJSREM (International Journal, Peer-Reviewed)
June 30, 2026 – Present
Survey on Federated Learning
IJSREM (International Journal, Peer-Reviewed)
June 30, 2026 – Present
Cultural Fit Analysis
The candidate's diverse experience across industry (Simplify Healthcare, Veritas LLC) and academia (Savitribai Phule Pune University), coupled with personal projects and publications, demonstrates a broad interest in AI/ML and a strong commitment to the field. Their work on privacy-preserving ML (Federated Learning, Differential Privacy) aligns with ethical AI development, which is a positive cultural indicator. The variety of roles and technologies used suggests adaptability and a willingness to explore different facets of AI engineering.
Soft Skills & Operational Fit
The candidate's experience in Agile sprints, cross-functional team collaboration, code reviews, and debugging production issues suggests strong operational fit and teamwork skills. Their research background and project diversity indicate a proactive, problem-solving attitude and a drive for innovation.