Summary
Pavel Zanin is a Data Scientist and ML Engineer with a decade of experience building production-grade AI solutions, currently focused on computer vision and large-scale model training for a leading pharmaceutical client at EPAM Systems. He combines deep expertise in Python, PyTorch/TensorFlow, and cloud GPU orchestration (AWS, Databricks, Horovod) with hands-on deployment skills using MLflow, TorchServe/TensorFlow Serving, and Docker to close the loop from training to monitoring. Prior roles include developing digital twins and real-time ML microservices for industrial IoT at Gazprom Neft and leading data-driven product development across GIS, PLM, and web apps. Pavel is comfortable optimizing cost and performance of GPU workloads and managing model lifecycles, and he brings an unusual blend of radioelectronics engineering and professional translation training that helps him bridge technical and cross-functional communication. He’s actively seeking Big Data projects where he can both design novel ML models and implement efficient middle-end microservices to serve them.
10 years of coding experience
10 years of employment as a software developer
Master’s Degree, Foreign languages, Translator in subject of professional communications (eng. lang.), Master’s Degree, Foreign languages, Translator in subject of professional communications (eng. lang.) at Tomsk State University of Control Systems and Radioelectronics
English, Russian