Machine Learning Engineer, Capital Underwriting

📋 Description

• Design state-of-the-art ML models for underwriting and portfolio management.
• Build systems to speed up deployment of new models.
• Experiment with ML models using PyTorch and TensorFlow.
• Develop pipelines to train and evaluate models offline and online.
• Integrate ML models into production with scalability and reliability.
• Collaborate with product and strategy to implement new features.

🎯 Requirements

• 5+ years building and shipping ML systems in production
• Proficient in PyTorch, TensorFlow, XGBoost, Spark
• Knowledge of ML algorithms and architectures
• Hands-on design, training, and evaluation of models
• Productionizing and deploying models at scale
• Orchestrating large-scale data pipelines and datasets