🛠 Tech Stack

💼 About This Role

You'll lead the design of scalable ML infrastructure at Upstart, building tools that accelerate model development for a leading AI lending marketplace. Your work will directly improve predictive accuracy, enabling fairer credit decisions for millions. This role combines deep ML engineering with cross-functional leadership to multiply the impact of every ML team.

🎯 What You'll Do

• Design and build a unified embeddings platform for training and serving representations.
• Streamline feature engineering pipelines to reduce manual steps and accelerate signal delivery.
• Develop automated continuous-learning systems for retraining and drift monitoring.
• Scale training pipelines to support larger datasets and faster experimentation.

📋 Requirements

• 7+ years of hands-on applied ML experience with production-scale modeling.
• End-to-end model development expertise: data prep, feature engineering, training, evaluation, deployment.
• Proficiency in Python and core ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, XGBoost).
• Master's degree or PhD in a quantitative discipline, or equivalent experience.

✨ Nice to Have

• Experience optimizing ML workflows using CUDA/GPU acceleration.
• Background in feature store design, embedding architecture, or synthetic data generation.
• Familiarity with modern experimentation frameworks and hyperparameter tuning tools.

🎁 Benefits & Perks

• 🏖️ Flexible Remote Work
• 🏢 Coworking Spaces Available
• 💰 Equity and Performance Bonuses
• 🧠 Learning and Development Budget
• ❤️ Health and Wellness Benefits