Manager, Machine Learning

📋 Description

• Own the ML model lifecycle from requirements to deployment.
• Translate business problems into ML solutions; define success and value.
• Design and maintain feature engineering pipelines for model dev.
• Drive experiment design and rigorous evaluation before and after launch.
• Monitor production models; track data drift; decide retraining.
• Cultivate a culture of learning across partner teams.
• Conduct design and code reviews to raise technical excellence.
• Hire, mentor, and coach data scientists.

🎯 Requirements

• 6+ years building and deploying ML systems in production.
• 2+ years mentoring and managing ML teams.
• Strong proficiency in Python and SQL.
• Strong ML fundamentals: model selection and evaluation.
• Hands-on with PyTorch, scikit-learn, XGBoost.
• Strong people leadership with cross-functional collaboration.
• Empathy and humility.

🎁 Benefits

• Experience building fraud detection or risk systems.
• Experience with AWS SageMaker.
• Experience with graph data/models (PyTorch Geometric).
• Model monitoring/observability tools (Arize).