Remote opportunity at
AffirmMachine Learning Engineer II (Underwriting ML)
Affirm operates as a financial technology company offering clear and predictable payment solutions over time without hidden fees or surprises. The Underwriting ML team builds and…
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About This Role
Affirm operates as a financial technology company offering clear and predictable payment solutions over time without hidden fees or surprises. The Underwriting ML team builds and enhances machine learning systems that evaluate repayment risk and expected value for every transaction in real time. As a Machine Learning Engineer II on this team, you will design and iterate on underwriting prediction models using tabular and sequential data approaches. Your work involves…
Job Description
Affirm operates as a financial technology company offering clear and predictable payment solutions over time without hidden fees or surprises. The Underwriting ML team builds and enhances machine learning systems that evaluate repayment risk and expected value for every transaction in real time.
As a Machine Learning Engineer II on this team, you will design and iterate on underwriting prediction models using tabular and sequential data approaches. Your work involves building feature pipelines, running offline experiments, and launching high-performing models into production environments with appropriate risk controls. You will also monitor model health, manage retraining workflows, and collaborate closely with Engineering, Risk Analytics, Product, and ML Platform groups.
This remote position suits professionals who enjoy working with distributed data systems, writing reliable Python code, and translating complex business scenarios into extensible technical solutions. Team members engage with global colleagues and participate in code reviews to maintain robust operational standards across large codebases.
Responsibilities
- Develop and iterate on underwriting prediction models utilizing sequential and tabular data approaches
- Build and scale feature pipelines and training datasets by leveraging proprietary and third-party signals
- Prototype modeling concepts, execute offline experiments, and push top-performing models to production with risk controls
- Integrate models into real-time or batch decision systems while boosting reliability, latency, and operational strength
- Instrument and track data and model health while establishing retraining and backtesting workflows
- Partner across Engineering, Risk Analytics, Product, and ML Platform to define requirements and communicate technical results
Requirements
- Possess either a total of 2+ years of experience as a machine learning engineer or a PhD in a relevant field
- Demonstrate strong Python skills and experience authoring production-quality code
- Bring experience building and assessing classification models, preferably gradient-boosted decision trees like LightGBM, XGBoost, or CatBoost
- Work with a deep learning framework such as PyTorch
- Utilize distributed data processing or parallel compute frameworks like Spark, Ray, or Dask
- Apply ML lifecycle tooling for training orchestration, experimentation, and model monitoring
- Use AI-powered developer tools like Claude Code or Cursor to accelerate daily development workflows
- Navigate large codebases, debug peer code, and deliver constructive code review feedback
Qualifications
- Either hold a Bachelor’s degree in a related field or possess equivalent practical experience
Core Skills
Benefits
- 100% subsidized medical coverage, dental, and vision for employees and their dependents
- Monthly stipends supporting technology setups, health, and wellness choices
- Flexible time off combined with generous holiday calendars
- Employee stock purchase plan allowing discounted stock purchases
- Base pay complemented by equity rewards
Frequently Asked Questions
Is this a remote position?
Yes, Affirm operates as a remote-first company, and this role can be performed from almost anywhere within the country of employment, though some positions may occasionally require in-person work at an office.
What is the salary range for this role?
The annual base pay for U.S. employees in CA, WA, NY, NJ, and CT ranges from $165,000 to $225,000, while the range for all other U.S. states is $146,000 to $206,000.
What experience is required to apply?
Applicants need either a total of two or more years of experience working as a machine learning engineer or a PhD in a relevant field, along with strong Python skills and experience with classification models.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.