Join Affirm's Underwriting ML team to develop and improve machine learning systems for real-time transaction decisions.
Skills & Technologies
AI in the day-to-day
Proficient in using AI-powered developer tools to accelerate iteration, debugging, and code quality.
Requirements
- Experience
- 2+ years
- Education
- Bachelor's degree
Benefits
Joblaze summary
In the role of Machine Learning Engineer II on the Underwriting ML team at Affirm, the individual will focus on developing and refining machine learning models that assess transaction risks in real-time. Key skills include strong Python programming, experience with classification models, and familiarity with deep learning frameworks like PyTorch, alongside tools for managing the ML lifecycle. This position is ideal for someone with at least two years of experience or a relevant PhD, who is comfortable collaborating across various teams and navigating complex codebases.
Joblaze insights
- Listed 16 days ago on Joblaze — tracked directly from Affirm's career page.
- Affirm has 217 other open roles including Legal Operations Analyst II, Manager, Software Engineering (Infra Foundations), Senior Software Engineer, Frontend (App Experience).
- 2641 active Python roles on Joblaze right now.
- 204 active Spark roles on Joblaze right now.
- 136 active PyTorch roles on Joblaze right now.
- Salary band is below the typical range for AI/ML roles (median ~$193,400).
- Pays more than 54% of the 1568 salaried Python roles we track (median $160,000). See Python salary trends
Quick facts
- Is the Machine Learning Engineer II (Underwriting ML) role remote?
- Yes — Affirm lists this as a fully remote position.
- What's the salary range?
- Affirm lists $165,000–$225,000 for this role.
- How much experience is required?
- At least 2 years of relevant experience for this Machine Learning Engineer II (Underwriting ML) role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Airflow, CatBoost, Dask, Kubeflow, LightGBM, MLflow.
- What seniority level is this role?
- Affirm targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Machine Learning Engineer II (Underwriting ML) role at Affirm.
From the original posting
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
#LI-Remote
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.
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.
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