Remote Underwriting ML Engineer — Real-Time Risk Models

Affirm; Houston (TX); On-site; USD 146,000 - 206,000; Full time

Benefits offered by this job

Health coverage

Stipends for tech setup

Time off and holidays

ESPP

Job summary

Affirm is seeking an experienced ML Engineer for the Underwriting team to build real-time decision systems that assess repayment risk at checkout. You will develop models for tabular and sequential data, create scalable feature pipelines, and push high‑performing approaches into production with robust monitoring.

You will work with data and platform teams to prototype ideas, run offline experiments, and ensure reliable, scalable production deployment while collaborating with cross‑functional

Qualifications

• 2+ years of experience as a machine learning engineer or a PhD in a relevant field.
• Proficient in Python and production-grade coding practices.
• Experience building and evaluating models for classification problems (gradient-boosted trees or similar).
• Experience with a deep learning framework (PyTorch preferred).
• Experience with distributed data processing/parallel compute (Spark preferred).
• Experience with ML lifecycle tooling (Kubeflow, Airflow, MLflow, etc.).
• Proficiency with AI-powered developer tools to accelerate iteration and code quality.
• Ability to work across multiple software components and write clear, well-tested code.
• Strong communication skills for collaboration across teams.
• Bachelor’s degree or equivalent practical experience.

Responsibilities

• Develop and iterate on underwriting prediction models for tabular and sequential data.
• Build and scale feature pipelines and training datasets with data/platform teams.
• Prototype modeling ideas, run offline experiments, and push best approaches into production with risk controls.
• Productionize models by integrating into batch/real-time decision systems and improving reliability.
• Instrument and monitor model and data health and design retraining workflows.
• Collaborate with Engineering, Risk Analytics, Product, and ML Platform to communicate results.

Skills

Python

Production‑quality code

LightGBM/XGBoost/CatBoost

PyTorch

Spark

Ray/Dask

ML lifecycle tooling

Kubeflow/Airflow/MLflow

AI developer tools

code reviews

communication

Education

Bachelor's degree or equivalent practical experience

Tools

LightGBM

XGBoost

CatBoost

Job description

Affirm is seeking an experienced ML Engineer for the Underwriting team to build real-time decision systems that assess repayment risk at checkout. You will develop models for tabular and sequential data, create scalable feature pipelines, and push high‑performing approaches into production with robust monitoring.

You will work with data and platform teams to prototype ideas, run offline experiments, and ensure reliable, scalable production deployment while collaborating with cross‑functional