Senior Machine Learning Engineer; ML Underwriting

Senior Staff 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 hidden fees or compounding interest.

Join the team as a Senior Staff Machine Learning Engineer and become a pivotal part of our innovative ML team focused on responsible and accessible financial products.

• Define and drive multi-year, multi-team technical strategy for machine learning across the organization, ensuring alignment with company-wide priorities and influencing partner teams and platforms.
• Lead the design, implementation, and scaling of advanced ML systems, setting the architectural direction for complex, cross-functional initiatives and ensuring reliability, extensibility, and performance.
• Partner deeply with ML Platform, product, engineering, and risk leaders to shape long-term modeling capabilities, define new opportunities for ML impact, and guide infrastructure evolution needed for next‑generation ML methods.
• Provide broad technical leadership across the ML organization, mentoring senior engineers, elevating design and code quality, and spreading ML expertise through documentation, talks, and cross‑org guidance.
• Drive clarity and alignment on ambiguous, high‑stakes technical decisions, resolving cross‑team tensions, balancing competing priorities, and exercising judgment optimized for the broader engineering organization.
• Champion operational and system excellence, owning the long-term health, availability, and evolution of critical ML systems and ensuring robust testing, monitoring, and reliability practices across teams.

• 10+ years of experience researching, designing, deploying, and operating large‑scale, real-time machine learning systems, with a proven record of driving technical innovation and delivering measurable business impact. Relevant PhD can count for up to 2 YOE.
• Experience leading end‑to‑end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment. Familiarity with distributed frameworks such as Spark, Ray, or similar large‑scale data processing systems.
• Proficiency in Python and ML frameworks, including PyTorch and XGBoost, and experience with ML tooling for training orchestration, experimentation, and model monitoring (Kubeflow, MLflow, etc.).
• Strong understanding of representation learning and embedding‑based modeling, neural‑network‑based sequence modeling (Transformers, recurrent, attention‑based models) and multi‑task learning systems.
• Hands‑on experience with large‑scale distributed ML infrastructure, including streaming or batch data ingestion, feature stores, feature engineering, training pipelines, model serving, inference infrastructure, monitoring, and automated retraining.
• Strong technical leadership: defining long‑term strategy, guiding research direction, and aligning work across teams, recognized as a trusted expert who can drive clarity and execution.
• Exceptional judgment, collaboration, and communication skills, enabling effective technical discussions with engineers, researchers, and executives. Mentoring senior engineers and fostering technical excellence.
• Strong verbal and written communication skills supporting effective collaboration across a global engineering organization.
• Equivalent practical experience or a Bachelor’s degree in a related field.

• Seniority level:
  Mid‑Senior
• Employment type:
  
  Full‑time
• Job function:
  Engineering and Information Technology

Pay Grade: R

Equity Grade: 15

Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits including 100% subsidized medical coverage, dental and vision for you and your dependents.

USA base pay range (CA, WA, NY, NJ, CT) per year: $260,000 - $310,000

USA base pay range (all other U.S. states) per year: $232,000 - $282,000

Remote. Most roles are remote; however, occasional on‑site presence may be required for assigned office.

• Health care coverage – the company covers all premiums for all levels of coverage…