Senior Machine Learning Engineer, ML Underwriting

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.

Join the Affirm team as a Senior Machine Learning Engineer and contribute to the success of our ML Underwriting team. We are the driving force behind Affirm's core value proposition, leveraging cutting-edge machine learning to assess creditworthiness throughout the life cycle of loan applications. 

As a Senior Machine Learning Engineer on our team, you will be at the forefront of developing high-quality, production-ready models that play a central role in our decision-making processes. Your contributions will be instrumental in shaping our financial landscape. If you have a strong interest in machine learning and enjoy challenging work, Affirm is the place for you!

What you’ll do

• Use Affirm’s proprietary and other third party data to develop machine learning models that predict the likelihood of default and make an approval or decline decision to achieve business objectives

• Partner with platform and product engineering teams to build model training, decisioning, and monitoring systems 

• Research ground breaking solutions and develop prototypes that drive the future of credit decisioning at Affirm

• Implement and scale data pipelines, new features, and algorithms that are essential to our production models

• Collaborate with the engineering, credit, and product teams to define requirements for new products

What we look for

• 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 with experience in 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 and the capability to drive cross-functional requirements with product and engineering teams

• Persistence, patience and a strong sense of responsibility – we build the …