Machine Learning Engineer II (Underwriting ML)

<div class="content-intro"><p>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.</p></div><div> <p>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.</p> </div> <div> <p>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.</p> <p>&nbsp;</p> <p><strong>What you’ll do</strong></p> <p>- You will develop and iterate on underwriting prediction models using a mix of approaches for tabular and sequential data</p> <p>- You will build and scale feature pipelines and training datasets from proprietary and third-party signals, partnering with data and platform teams when needed.</p> <p>- You will prototype new modeling ideas and features, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.</p> <p>- You will help productionize models: integrate into batch and/or real-time decision systems, and improve reliability, latency, and operational robustness.</p> <p>- You will instrument and monitor model and data health, and help define retraining/backtesting workflows</p> <p>- 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.</p> <p>&nbsp;</p> <p><strong>What we look for</strong></p> <p>- You have a total of 2+ years of experience as a machine learning engineer or a PhD in a relevant field.</p> <p>- Strong Python skills and experience writing production-quality code.</p> <p>- Experience building and evaluating models for classification problems (preferably gradient-boosted decision trees like LightGBM/XGBoost/CatBoost, or similar).</p> <p>- Experience with a deep learning framework (PyTorch preferred).</p> <p>- Experience working with distributed data processing or parallel compute frameworks (Spark preferred; Ray/Dask or similar).</p> <p>- Experience with ML lifecycle tooling for training orchestration, experimentation, and model monitoring (e.g., Kubeflow, Airflow, MLflow, or equivalent internal platforms).</p> <p>- 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.</p> <p>- 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.</p> <p>- You are comfortable navigating a large code base, debugging others' code, and providing feedback to other engineers through code reviews.</p> <p>- Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders.</p> <p>- You have strong verbal and written communication skills that support effective collaboration with our global engineering team.</p> <p>- This position requires either equivalent practical experience or a Bachelor’s degree in a related field.</p> </div> <p>Pay Grade - L<br>Equity Grade - 5<br><br>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.&nbsp;<br><br>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).<br><br>CAN base pay range per year: $133,000 - $183,000</p> <p>Location - Remote Canada</p> <p>This remote role is open only to candidates residing in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland a