Summary
Michael Collis is a technology leader specializing in machine learning data engineering, currently directing ML and data infrastructure at Wonder. With 9 years of experience across Google, Blue Apron, and startup-scale ML teams, he drives production-grade ML, personalization, NLP, and large-scale distributed systems. He is proficient across Python, Java, Go, SQL, and more, with hands-on work in Airflow, Kafka, Spark, Flink, Kubernetes, AWS/GCP, and ML tooling like TensorFlow and Langchain. His work emphasizes privacy, security, and compliance while delivering high-performance, scalable data pipelines and cloud infrastructure. An academic and industry hybrid, he is a PhD candidate in Computer Science at the University of Pennsylvania and holds an MS in CS from Penn, with additional CS studies at Stanford and Georgetown and a BA in Economics from Cornell. Based in New York, he blends rigorous research with practical execution to turn complex ML challenges into reliable, auditable systems.
9 years of coding experience