Summary
Mark Vinogradov is a Senior Software Engineer with 11 years of experience building full-stack web applications and production ML tooling, blending Python backends (Celery), React frontends, and orchestration via Kubernetes, Helm, and Airflow. He has shipped scalable data and ML infrastructure at startups and scaleups—designing DB migration tooling, ML model quality monitoring with Spark on GCP, and crowd-sourced image annotation pipelines for supervised/semi-supervised vision. Notable work includes agritech ML systems used by ~100k users and a soil-sampling method that became a key commercial feature in LATAM, plus cost- and performance-driven refactors that cut AWS costs by ~43% while improving pipeline speed. Comfortable across system design, async CPU-heavy schedulers, gRPC/LangChain integrations and monitoring, he combines hands-on implementation with product-focused outcomes. Based in Tbilisi, he pairs an MS in Data Science with a background in low-shot image recognition and practical experience taking ML services from prototype to pilots with major enterprise customers.
11 years of coding experience
7 years of employment as a software developer
Master of Science - MS Data Science, Master of Science - MS Data Science at Skolkovo Institute of Science and Technology
Bachelor's degree Computer Science, Bachelor's degree Computer Science at Moscow Institute of Physics and Technology (State University) (MIPT)
English, Russian