I am a Machine Learning, MLOps, and Data Engineer who bridges the gap between data science and production-grade software engineering. I specialize in designing scalable data infrastructure, building real-time event-driven streaming pipelines, and deploying robust machine learning solutions.
My work centers on three main domains:
- Enterprise Data Streaming & Infrastructure: Architecting decoupled microservices and real-time ingestion pipelines (Kafka, Docker, FastAPI) capable of processing high-density time-series data, automated batch workflows, and historical data backfills.
- Cloud & Production MLOps: Designing and deploying containerized applications within cloud environments (Azure), with a strict focus on reproducible deployment pipelines, experiment tracking (MLflow), and optimized model serving.
- Generative AI & Autonomy: Engineering robust Retrieval-Augmented Generation (RAG) systems and building intelligent text-processing pipelines to automate workflows and optimize enterprise processes.
Backed by a proven track record in both advanced academic research and hands-on industry product development, my primary focus is creating stable, automated backend systems that process data reliably at scale.