Machine Learning Engineer II (Underwriting ML)

Affirm; Boise (ID); Remote; USD 150,000 - 206,000; Full time

Benefits offered by this job

Health benefits

Flexible Spending Wallets

Time off

ESPP

Job summary

Affirm is reinventing credit to make it more honest and friendly, enabling flexible pay-later options. On the Underwriting ML team, you’ll build and improve machine learning systems that make real-time transaction decisions, evaluating repayment risk and expected value of each checkout.

You will work with ML engineers, data and platform teams to take models from idea to prototype to production, with monitoring as user behavior and macro conditions evolve.

Qualifications

• 2+ years of experience as a machine learning engineer or a PhD in a relevant field
• Strong Python skills and production-quality code
• Experience building and evaluating classification models (tree-based like LightGBM/XGBoost/CatBoost)
• Experience with a DL framework (PyTorch preferred)
• Experience with distributed data processing (Spark preferred)
• ML lifecycle tooling for training orchestration, experimentation, and monitoring
• Familiarity with AI-powered developer tools for rapid iteration and quality code
• Ability to translate business problems into robust, multi-component software solutions
• Strong communication skills for collaboration with global teams
• Bachelor’s degree or equivalent practical experience in a related field

Responsibilities

• Develop and iterate underwriting prediction models for tabular and sequential data
• Build feature pipelines and training datasets from proprietary and third-party signals
• Prototype modeling ideas, run offline experiments, and productionize top approaches
• Productionize models in batch or real-time decision systems with reliability and latency focus
• Instrument and monitor model and data health and define retraining workflows
• Collaborate with Engineering, Risk Analytics, Product and ML Platform to align requirements and communicate results

Skills

Python

Production-grade code

Model evaluation

PyTorch

Spark

Kubeflow/Airflow/MLflow

Code reviews/ownership

Education

Bachelor’s degree or equivalent practical experience

Tools

LightGBM

XGBoost

CatBoost

PyTorch

Spark

Job description

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.

On the Underwriting ML team, you’ll build and improve machine learning systems that make real-time transaction decisions, assessing the repayment risk and expected value of every affirm checkout. You’ll work closely with experienced ML engineers, platform partners, and cross-functional stakeholders to take models from idea to prototype to production, and to keep them healthy with strong measurement and monitoring as user behavior and macroeconomic conditions evolve.

What You’ll Do

• You will develop and iterate on underwriting prediction models using a mix of approaches for tabular and sequential data
• You will build and scale feature pipelines and training datasets from proprietary and third-party signals, partnering with data and platform teams when needed.
• You will prototype new modeling ideas and features, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
• You will help productionize models: integrate into batch and/or real-time decision systems, and improve reliability, latency, and operational robustness.
• You will instrument and monitor model and data health, and help define retraining/backtesting workflows
• You will collaborate across Engineering, Risk Analytics, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non-technical audiences.

What We Look For

• You have a total of 2+ years of experience as a machine learning engineer or a PhD in a relevant field.
• Strong Python skills and experience writing production-quality code.
• Experience building and evaluating models for classification problems (preferably gradient-boosted decision trees like LightGBM/XGBoost/CatBoost, or similar).
• Experience with a deep learning framework (PyTorch preferred).
• Experience working with distributed data processing or parallel compute frameworks (Spark preferred; Ray/Dask or similar).
• Experience with ML lifecycle tooling for training orchestration, experimentation, and model monitoring (e.g., Kubeflow, Airflow, MLflow, or equivalent internal platforms).
• Proficient in using AI-powered developer tools (e.g., Claude Code, Cursor, or similar) to accelerate iteration, debugging, and code quality as part of day-to-day development workflows.
• You have mastered taking a simple problem or business scenario into a solution that interacts with multiple software components, and executing on it by writing clear, easily understood, well tested and extensible code.
• You are comfortable navigating a large code base, debugging others' code, and providing feedback to other engineers through code reviews.
• Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders.
• You have strong verbal and written communication skills that support effective collaboration with our global engineering team.
• This position requires either equivalent practical experience or a Bachelor’s degree in a related field

Pay Grade - L

Equity Grade - 6

Employees new to affirm typically come in at the start of the pay range. affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.

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: $165,000 - $225,000

USA base pay range (all other U.S. states) per year: $146,000 - $206,000

Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.

Benefits

We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:

• 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 allowing you to take time off to rest and recharge
• ESPP - An employee stock purchase plan enabling you to buy shares of affirm at a discount

We believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, affirm will consider for employment qualified applicants with arrest and conviction records.