ML Engineer II

About the Company

Affirm is a pioneering financial technology company committed to transforming the credit industry by making it more transparent, honest, and user-friendly. Our mission is to provide consumers with flexible, transparent payment options that eliminate hidden fees and avoid the pitfalls of compounding interest. By leveraging innovative technology and data-driven insights, Affirm empowers millions of users across the United States to make smarter financial decisions. We foster a dynamic, inclusive, and remote-first work environment that encourages continuous learning, collaboration, and growth.

About the Role

We are seeking a talented Machine Learning Engineer to join our Underwriting ML team. In this role, you will be instrumental in developing and enhancing machine learning systems that facilitate real-time transaction decisions. Your primary focus will be on assessing repayment risks and calculating the expected value of each Affirm checkout, ensuring our underwriting models are accurate, reliable, and scalable. You will collaborate closely with experienced ML engineers, data scientists, platform teams, and cross-functional stakeholders to take models from conception to production, maintaining their health through robust measurement and monitoring practices. This position offers a unique opportunity to work on impactful, high-visibility projects that directly influence our core product offerings and customer experience.

Qualifications

• 2+ years of experience as a machine learning engineer or a PhD in Computer Science, Data Science, Statistics, or a related field
• Proficiency in Python with experience writing production-quality code
• Experience building and evaluating classification models, preferably gradient-boosted decision trees such as LightGBM, XGBoost, or CatBoost
• Hands-on experience with deep learning frameworks, with a preference for PyTorch
• Knowledge of distributed data processing or parallel compute frameworks, such as Spark, Ray, or Dask
• Experience with ML lifecycle tools like Kubeflow, Airflow, MLflow, or similar platforms
• Familiarity with AI-powered developer tools to accelerate development workflows
• Strong problem-solving skills with the ability to translate business scenarios into technical solutions
• Ability to navigate large codebases, perform debugging, and conduct code reviews effectively
• Excellent communication skills, both verbal and written, to collaborate with technical and non-technical teams
• Equivalent practical experience or a Bachelor’s degree in a relevant field

Responsibilities

• Develop, iterate, and optimize underwriting prediction models using diverse approaches for tabular and sequential data
• Build and scale feature pipelines and training datasets from proprietary and third-party signals in collaboration with data and platform teams
• Prototype innovative modeling ideas and features, conduct offline experiments, and implement the best approaches into production with appropriate risk controls
• Integrate models into batch and real-time decision systems, enhancing their reliability, latency, and operational robustness
• Instrument and monitor model performance and data health, establishing workflows for retraining and backtesting
• Collaborate across Engineering, Risk Analytics, Product, and ML Platform teams to define requirements, evaluate tradeoffs, and communicate findings effectively
• Ensure models adhere to compliance and risk management standards while maintaining high performance

Benefits

• Comprehensive health care coverage, including premiums paid for you and your dependents
• Flexible Spending Wallets with stipends for technology, food, lifestyle needs, and family expenses
• Generous time off policies, including vacation and holidays, to promote work-life balance
• Participation in the Employee Stock Purchase Plan (ESPP) with discounts on Affirm shares
• Remote-first work environment with opportunities to work almost anywhere within the United States
• Inclusive culture that values diversity and provides reasonable accommodations during the hiring process
• Additional wellness and tech stipends designed to support your personal and professional growth