Machine Learning Engineer II (Underwriting ML)

Affirm; United States; Remote; USD 95,000 - 131,000; Full time

Benefits offered by this job

Health coverage

Flexible Spending Wallets

Time off

Employee stock purchase plan

Job summary

Affirm, Inc. is seeking an ambitious ML Engineer on the Underwriting team to build real-time decisioning systems for credit risk.

You will develop models, scale feature pipelines, and bring ideas from concept to production with strong monitoring and governance. You will collaborate with Engineering, Risk Analytics, Product, and ML Platform to define requirements, compare tradeoffs, and clearly communicate results to technical and non-technical audiences.

Qualifications

• 2+ years of experience as ML engineer or a PhD in a relevant field.
• Strong Python skills and production-quality code.
• Experience building/evaluating models for classification (GBDTs like LightGBM/XGBoost/CatBoost).
• Experience with a deep learning framework (PyTorch).
• Experience with distributed data processing (Spark).
• Experience with ML lifecycle tooling (Kubeflow, Airflow, MLflow).
• Proficient in AI-powered developer tools (Claude Code, Cursor).
• Ability to write clear, tested, extensible code across components.
• Strong verbal and written communication for global teams.
• Bachelor’s degree or equivalent practical experience.

Responsibilities

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

Skills

Python

Production code

Model monitoring

Distributed data processing

PyTorch

Spark

ML lifecycle tooling

Code reviews

Communication

Ownership

Education

Bachelor’s degree or PhD in related field

Tools

LightGBM

XGBoost

CatBoost

Kubeflow

Airflow

MLflow

Claude Code

Cursor

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.

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 - 5

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 monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by affirm holdings, inc. (parent company).

CAN base pay range per year: $133,000 - $183,000

Location - Remote Canada

This remote role is open only to candidates residing in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, or Saskatchewan.

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.

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.

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.