Machine Learning Engineer II (Underwriting ML)

About the Position

Machine Learning Engineer II (Underwriting ML)

Remote Canada

At Affirm, we exist for the moments that matter-giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most.

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.

Responsibilities

• Develop and iterate on underwriting prediction models using a mix of approaches for tabular and sequential data.
• Build and scale feature pipelines and training datasets from proprietary and third-party signals, partnering with data and platform teams when needed.
• Prototype new modeling ideas and features, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
• Help productionize models: integrate into batch and/or real-time decision systems, and improve reliability, latency, and operational robustness.
• Instrument and monitor model and data health, and help define retraining/backtesting workflows.
• 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.

Requirements

• 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.
• Demonstrated ability to take 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.
• Comfortable navigating a large code base, debugging others' code, and providing feedback to other engineers through code reviews.
• Experience demonstrating ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders.
• Strong verbal and written communication skills that support effective collaboration with our global engineering team.
• Bachelor’s degree in a related field or equivalent practical experience.

We Offer

• Competitive base pay range per year: $133,000 - $183,000 (USD).
• Health coverage at no cost: We cover 100% of premiums for employees and their dependents.
• Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.
• Flexible time off and generous holiday calendars.
• Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.

About the Company

Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.

Our benefits reflect our commitment to care, transparency, and flexibility. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help.

For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law.

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