lakshay chauhan

I’m a Machine Learning Engineer with 4+ years of experience architecting end-to-end solutions across Natural Language Processing (NLP), Deep Learning, Large Language Models (LLMs), and Generative AI. I build dependable pipelines—from data and features to deployable models—so teams can ship reliable, measurable improvements.

I’m especially strong in MLOps and LLMOps, handling model versioning, CI/CD pipelines, prompt versioning, experiment tracking (MLflow), and production monitoring. I combine containerization and orchestration (Docker, Kubernetes) with robust evaluation and tuning practices to keep AI systems stable over time.

In my roles, I’ve delivered practical, business-impacting agentic and retrieval-augmented solutions, including secure RAG-based LLM chatbots, investigative self-service agents for trading pipelines, and automated matching/categorization to reduce manual effort. I bring a hands-on engineering mindset in Python-based ML stacks and modern cloud tooling to turn complex problems into scalable AI capabilities.