Alex Rodarmel

I’m a senior AI/ML and data engineer with over 12 years of experience designing, building, and operating production-grade data platforms and machine learning systems across healthcare, finance, and SaaS. My work spans the full lifecycle of data and ML systems—from raw data ingestion and modeling to training, deploying, and monitoring models at scale. I’ve led the design of cloud-native architectures using AWS, Azure, and GCP, and I’m experienced with modern data stacks including Snowflake, Spark, Kafka, Airflow, and Kubernetes.

On the machine learning side, I’ve worked extensively with classic ML, deep learning, and more recently LLM-powered and RAG-based applications. I’ve built MLOps and LLMOps pipelines using tools like MLflow, Docker, and CI/CD to ensure reproducibility, reliability, and continuous improvement in production. I enjoy bridging the gap between data engineering and machine learning, and I’m particularly proud of leading teams to deliver systems that are not only technically strong but also trusted and widely used by stakeholders.

I’m most interested in roles where data and AI are central to the product, where teams value strong engineering practices, collaboration, and clear ownership, and where technology is applied thoughtfully to create meaningful impact. I’m especially drawn to mission-driven or product-focused companies that care deeply about data quality, scalability, and responsible use of AI.