Machine Learning Engineer II (Underwriting ML)

Affirm
Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, Saskatchewan
Workplace: RemoteFull timeUSD 133,000 - 183,000 annuallyFunction: Data Science & Machine LearningExperience: 2+ yearsEducation: bachelorsSkills: ["Communication","Collaboration","Ownership"]

Build and improve underwriting machine learning systems that power real-time transaction decisions. Develop prediction models for repayment risk and expected value, create feature pipelines and training datasets from proprietary and third-party signals, and run offline experiments before productionizing with strong risk controls. Instrument and monitor model and data health, define retraining/backtesting workflows, and collaborate across Engineering, Risk Analytics, Product, and ML Platform.

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Affirm
Affirm
1 day ago

Machine Learning Engineer II (Underwriting ML)

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Last checked: 3 hours agoStatus: Live

Job Summary

Build and improve underwriting machine learning systems that power real-time transaction decisions. Develop prediction models for repayment risk and expected value, create feature pipelines and training datasets from proprietary and third-party signals, and run offline experiments before productionizing with strong risk controls. Instrument and monitor model and data health, define retraining/backtesting workflows, and collaborate across Engineering, Risk Analytics, Product, and ML Platform.
Location: Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, Saskatchewan
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Develop and iterate on underwriting prediction models for tabular and sequential data.
  • •Build and scale feature pipelines and training datasets from proprietary and third-party signals.
  • •Prototype new modeling ideas and features, run offline experiments, and drive best approaches into production with risk controls.
  • •Productionize models by integrating into batch and/or real-time decision systems and improving reliability, latency, and operational robustness.
  • •Instrument and monitor model and data health and help define retraining/backtesting workflows; collaborate with engineering, risk analytics, product, and ML platform to evaluate tradeoffs and communicate results.

Pay and Benefits

Salary: USD 133,000 - 183,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionEsppPaid Leave

Key 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 classification models, preferably gradient-boosted decision trees (LightGBM/XGBoost/CatBoost or similar).
  • •Experience with a deep learning framework (PyTorch preferred).
  • •Experience with distributed data processing/parallel compute (Spark preferred) and ML lifecycle tooling for training, experimentation, and monitoring (e.g., Kubeflow, Airflow, MLflow).
Experience:2+ yearsMachine learning
Education:Bachelor's
Skills:CommunicationCollaborationOwnership
Languages:English
Tech Stack:PythonLightGBMXGBoostCatBoostPyTorchSparkRayDaskKubeflowAirflowMLflowClaude CodeCursor

Company Brief

Affirm
Provides point-of-sale lending and buy-now-pay-later (BNPL) solutions for consumers and merchants, enabling installment payments, consumer financing, and embedded financial services through APIs and partnerships with retailers and platforms.
Industry: Lending
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Francisco, United States
Founded: 2012
WebsiteLinkedIn