Junaid Malik

I’m a Machine Learning Engineer with over 7 years of experience building and deploying scalable AI solutions across deep learning, NLP, computer vision, and Generative AI. I design end-to-end ML pipelines, optimize model performance, and deploy reliable systems using MLOps and modern software engineering practices—especially with LLMs, RAG pipelines, and distributed data architectures.

In my current role as Lead AI/ML Engineer at H2O.ai, I develop scalable systems for model evaluation, monitoring, and performance optimization across production environments. I’ve designed retrieval-augmented generation (RAG) pipelines using embeddings and vector databases, improved LLM output quality with prompt engineering, and established LLMOps best practices like model versioning, evaluation workflows, and continuous monitoring. I’ve also led large-scale experimentation platforms to train and evaluate deep learning and transformer-based models, while collaborating with engineering and product teams to integrate AI into production.