Machine Learning Engineer (Servicing ML)

Role Overview

Join Affirm’s Servicing ML team as a Machine Learning Engineer. You will build and improve AI systems that automate customer operations, partnering with cross-functional stakeholders to take models from idea to production.

Key Missions / Responsibilities

• Build and improve machine learning and AI systems to automate customer operations.
• Collaborate with ML engineers and cross-functional stakeholders to deliver models end-to-end.
• Develop AI systems to automate dispute and chargeback processing using structured evidence.
• Take ownership of quality and iteration, including code review feedback and debugging across a large codebase.

Requirements

• 2+ years of experience as a Machine Learning Engineer.
• Strong Python skills and experience writing production-quality code.
• Experience with ML lifecycle tooling for:
  • Training orchestration
  • Experimentation
  • Model monitoring (e.g., Kubeflow, Airflow, MLflow, or equivalent internal platforms).
• Familiarity with document and unstructured data processing (e.g., PDF/image extraction, text parsing).
• Ability to turn business problems into solutions integrating multiple software components with clear, tested, extensible code.
• Experience building and evaluating models for tabular classification (preferably LightGBM/XGBoost/CatBoost).
• Experience building applications with LLM APIs (e.g., OpenAI, Anthropic), including:
  • Structured extraction
  • Prompt engineering
  • Orchestration frameworks such as LangChain or LangGraph.
• Strong communication skills for collaboration with a global engineering team.
• Either equivalent practical experience or a Bachelor’s degree in a related field.

Nice-to-Haves

• Proficiency with AI-powered developer tools (e.g., Claude Code, Cursor) to speed iteration, debugging, and code quality.