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
Robust professional 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

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