Vladimir Starostenkov is a Solutions Architect based in Seattle with 13 years of experience designing and operationalizing ML systems across enterprise and R&D settings. He combines deep embedded and firmware roots with a modern focus on MLOps, cloud data engineering and production ML—backed by certifications from Databricks, AWS ML Specialty and Google Cloud Data Engineer. At EPAM and Toptal he translates complex data science prototypes into robust, scalable pipelines and deployment patterns, drawing on earlier roles building big data platforms and permissioned blockchain proofs-of-concept. Comfortable across C/C++ firmware, Hadoop/TensorFlow stacks and cloud-native ML tooling, he uniquely bridges low-level performance optimization and high-level ML architecture. Colleagues rely on him for pragmatic architectures that prioritize reproducibility and operational resilience, a skill honed from shipping both embedded devices and distributed ML products.
13 years of coding experience
11 years of employment as a software developer
Control in Engineering and Organization Systems, Control in Engineering and Organization Systems at Institute for Control Sciences RAS
BSc, Applied Mathematics and Physics, BSc, Applied Mathematics and Physics at Moscow Institute of Physics and Technology (State University) (MIPT)
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Vladimir Starostenkov - Solutions Architect at Toptal