Principal Machine Learning Engineer
Principal Machine Learning Engineer
Principal Machine Learning Engineer
Upstart
Upstart is a leading AI lending marketplace focused on expanding access to affordable credit through innovative technology. The company is forming a new Applied Machine Learning team within its Decisioning organization to enhance model accuracy in underwriting systems. This role involves technical leadership in applied ML initiatives, driving improvements in pricing accuracy and borrower conversion through advanced machine learning techniques.
Qualification
- Proven experience in applied machine learning and model development.
- Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch).
- Experience with GPU programming and CUDA for model training optimization.
- Expertise in feature engineering and data preprocessing techniques.
- Ability to collaborate effectively with cross-functional teams, including engineering and data science.
Responsibility
- Serve as the technical lead for applied ML initiatives that improve the accuracy, precision, and recall of underwriting models.
- Design and implement advanced ML training strategies, including AutoML, ensemble learning, and temporal modeling techniques.
- Drive GPU-accelerated experimentation, including CUDA-based training optimization and embedding fine-tuning.
- Build robust data preprocessing and feature engineering pipelines that can be used in both experimentation and production.
- Influence modeling strategy through close collaboration with Pricing Engineering and the ML Science organization.
- Deliver measurable improvements to model-driven business outcomes such as conversion rate, rate accuracy, and loan performance.
- Mentor future applied ML engineers and help define the long-term roadmap for ML excellence within Pricing.
