Mark Andreev

Accomplished Senior Software Engineer at Conundrum, London, specializing in optimizing ML systems and MLOps with Java, Python, Kubernetes, Spring, and Vert.x for Kafka & Clickhouse feature stores. Also proficient in PostgreSQL and Redis. Recognized for significant achievements, including a 3x improvement in popular queries, a 5x reduction in CPU load for Kafka subscription proxies, and a stellar 15x increase in query speed. I bring a deep understanding of trade-offs, balancing performance enhancements with resource efficiency.

Actively contributing to open-source projects such as Keycloak, Apache Camel, Apache Ignite, Clickhouse, Zipkin, and Tornado Swagger, with diverse contributions from implementing a fix for header override by Azure Storage Blob download consumer to advanced features like target encoding preprocessor and CatBoost inference integration.

Armed with a Master’s Degree in applied mathematics and computer science from Lomonosov Moscow State University, I am passionate about driving innovation in machine learning technologies.