Senior Machine Learning Engineer (Underwriting)

Job Description

Affirm is seeking a Senior Machine Learning Engineer to join their ML Underwriting team. This role is crucial in developing high-quality, production-ready models that assess creditworthiness and drive decision-making processes. The ideal candidate will have a strong interest in machine learning and enjoy challenging work.About the Company:Affirm is reinventing credit to make it more honest and friendly, offering consumers the flexibility to buy now and pay later without hidden fees or compounding interest.Role Involves:

• Developing machine learning models to predict the likelihood of default using Affirm’s proprietary and third-party data.
• Partnering with platform and product engineering teams to build model training, decisioning, and monitoring systems.
• Researching groundbreaking solutions and developing prototypes for future credit decisioning.
• Implementing and scaling data pipelines, new features, and algorithms essential to production models.
• Collaborating with engineering, credit, and product teams to define requirements for new products.

Requirements:

• 6+ years of experience as a machine learning engineer (relevant PhD can count for up to 2 YOE).
• Experience developing machine learning models at scale from inception to business impact.
• Proficiency in machine learning areas such as Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration.
• Strong engineering skills in Python and data manipulation skills like SQL.
• Experience using large-scale distributed systems like Spark or Ray.
• Experience using open-source projects and software such as scikit-learn, pandas, NumPy, XGBoost, PyTorch, Kubeflow.
• Experience with Kubernetes, Docker, and Airflow is a plus.
• Excellent written and oral communication skills.
• Persistence, patience, and a strong sense of responsibility.

What Affirm Offers:

• Health care coverage: Affirm covers all premiums for all levels of coverage for you and your dependents.
• Flexible Spending Wallets: Generous stipends for spending on Technology, Food, various Lifestyle needs, and family-forming expenses.
• Time off: Competitive vacation and holiday schedules.
• ESPP: An employee stock purchase plan.