I am an AI/ML Engineer with over a year of experience building and deploying intelligent systems that solve real-world problems.

I have worked across the full lifecycle of machine learning solutions, from raw data preparation and model development to production deployment and monitoring. I enjoy turning ideas into reliable systems that can scale and deliver measurable business value.

My experience includes data science, forecasting, retrieval-augmented generation, and applied machine learning. I have built pipelines for scoring, prediction, and search, and I am comfortable working with both classical ML and deep learning approaches.

I am especially interested in systems that combine reasoning, retrieval, and automation. I like designing solutions that are fast, robust, and practical, whether they are used for analytics, decision support, or user-facing AI products.

I have hands-on experience with Python, SQL, TensorFlow, PyTorch, FastAPI, Docker, Kubernetes, and cloud platforms. I also work with modern LLM and MLOps tooling to make experiments reproducible and deployments dependable.

I am open to remote, hybrid, and relocation opportunities, and I am looking for roles where I can continue growing as an AI/ML professional while contributing to impactful products and teams.