Summary
Koosha Tahmasebipour is a Sr. Staff Machine Learning Engineer with nine years of experience building end-to-end AI/ML solutions across healthcare, finance, telecom, e-commerce and publishing. He specializes in problem scoping, data architecture and feature engineering, and has a track record of taking models from MVP to production with close collaboration with SRE/DevOps teams. At Kinaxis he focuses on applying ML to complex supply chain problems, after having led near-real-time recommender systems and large-scale ML platforms at Viafoura and Rogers. His background includes hands-on work with MLOps tools (SageMaker, Databricks), distributed processing (Spark/EMR/Glue), and infrastructure as code (Terraform, Kubernetes). He blends academic rigor—a master’s thesis on disease-gene association—with practical engineering, often stepping into a data architect role to resolve messy production data challenges. Known for translating domain knowledge into actionable model features, he thrives on solving thorny, cross-functional problems that unlock business impact.
9 years of coding experience
13 years of employment as a software developer
Bachelor's Degree Computer Software Engineering, Bachelor's Degree Computer Software Engineering at Shahid Beheshti University
Master's Degree Computer Science, Master's Degree Computer Science at Brock University
High School Diploma Mathematics, High School Diploma Mathematics at National Organization for Development of Exceptional Talents (Sampad)
English, Persian