AI Engineer with 5 years of experience building production-grade machine learning and GenAI systems across search, retrieval, and agentic workflows. My work spans classical machine learning as well as modern generative AI techniques such as retrieval-augmented generation (RAG), hybrid search, and agent-based systems, with a strong focus on MLOps, evaluation, and scalable deployments.

I enjoy working across the full lifecycle of ML systems—from experimentation and model development to evaluation, deployment, monitoring, and production operations. I have built systems that combine traditional ML techniques with retrieval pipelines and LLM-based architectures to solve real-world problems at scale.

I am particularly interested in designing systems where machine learning, retrieval, and agentic workflows come together with robust MLOps and evaluation frameworks to enable reliable, high-quality AI applications in production.