Professional Overview
I’m an AI/ML Engineer passionate about building production-ready GenAI applications using LLMs, RAG pipelines, and scalable AI systems. I have hands-on experience with Python, LangChain, HuggingFace, FastAPI, Streamlit, and vector databases, along with projects involving conversational AI, evaluation pipelines, and deep learning. I enjoy solving re
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built AI-powered document and PDF processing workflows using Python and automati
- Developed and optimized NLP/LLM-based pipelines for content validation and data
- Worked with FastAPI, Streamlit, and backend systems to build scalable internal A
- Improved processing efficiency by debugging, optimizing, and automating producti
- Collaborated with teams to integrate AI solutions into real-world publishing and
Key Achievements / KPIs
- Reduced scientific manuscript processing cost by ~58% using optimized multimodal
- Cut invalid inference inputs by ~30% through anomaly detection preprocessing pip
- Improved extraction reliability by ~25% on complex table layouts via prompt opti
- Built scalable dual inference pipelines with batching, retries, and production-g
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
