Develop and validate machine-learning models and training pipelinesImplement model components, data pipelines, and evaluation systemsBuild reproducible programmatic workflows using Python and command-line toolsCreate and solve challenging machine-learning engineering tasksOptimize memory and throughput for existing machine learning systemsDebug numerical or system-level failures in implemented modelsVerify that implementations meet correctness and performance specificationsRequirements
Master's degree or PhD in a related quantitative disciplineStrong skilled or research experience in machine learningPractical proficiency with Python and coding agentsExperience at a recognized technology company or research organizationAbility to demonstrate depth with equivalent tools if necessaryExceptional open-source or academic experience is a plusWillingness to start tasks within 24 48 hours after onboarding