Rajesh Nemani

I am an AI/ML and Generative AI Engineer with 7 years of experience, focused on building intelligent applications using Python, Natural Language Processing (NLP), Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG). I enjoy solving real-world problems by combining machine learning, language technologies, and practical software engineering.

In my previous work as a GenAI/NLP Engineer, I contributed to HR knowledge retrieval and chatbot solutions, working on document processing, NLP pipelines, and AI-powered information access. My project work included reported improvements of 30% in RAG performance, 75% in chatbot response accuracy, and 20% in NLP processing efficiency.

I have also developed an AI-based multi-agent trading research system that combines market analysis, sentiment analysis, machine-learning-based regime detection, risk management, and monitoring. This project has given me hands-on experience with XGBoost, reinforcement learning concepts, agent coordination, audit logging, and decision-support dashboards.

Another key project is a freight-rate prediction solution built using approximately 48,000 historical records and 59 engineered features. I evaluated 10 regression models using time-series cross-validation and achieved a reported R² of 0.851 during model evaluation.

My core interests include Generative AI, RAG systems, LLM agents, AI evaluation and testing, NLP, applied machine learning, and building reliable AI applications. I am particularly interested in opportunities where I can develop practical AI solutions, improve answer quality and system reliability, and collaborate with engineering and product teams.

I am currently seeking full-time opportunities as a Generative AI Engineer, LLM Engineer, RAG Engineer, AI Engineer, or Machine Learning Engineer. I am open to remote opportunities in India and suitable international roles. I value continuous learning, clean engineering practices, measurable outcomes, and building AI systems that solve meaningful business problems.