Develop and validate machine-learning models and training pipelines Implement model components, data pipelines, and evaluation systems Build reproducible programmatic workflows using Python and command-line tools Create and solve challenging machine-learning engineering tasks Optimize memory and throughput for existing machine learning systems Debug numerical or system-level failures in implemented models Verify that implementations meet correctness and performance specifications Requirements

Master's degree or PhD in a related quantitative discipline Strong qualified or research experience in machine learning Practical proficiency with Python and coding agents Experience at a recognized technology company or research organization Ability to demonstrate depth with equivalent tools if necessary Exceptional open-source or academic experience is a plus Willingness to start tasks within 24 48 hours after onboarding

📌 Machine Learning Engineer | Remote (Winnipeg)
🏢 Crossing Hurdles
📍 Winnipeg