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    Home/Jobs/Machine Learning Engineer II (Servicing ML)

    Machine Learning Engineer II (Servicing ML)

    Affirm

    United States
    2+ years
    Today
    ₹17–22 LPA
    Full-time
    Remote

    Skills Required

    OpenAI
    LangChain
    Python
    LightGBM
    XGBoost
    CatBoost
    Kubeflow
    Apache Airflow
    MLflow

    Description

    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 Servicing ML team, you will build and improve machine learning and AI systems that automate customer operations. You will work closely with experienced ML engineers, platform partners, and cross-functional stakeholders.

    Company: Affirm

    Role: Machine Learning Engineer II (Servicing ML)

    Location: Remote US

    Experience:

    • 2+ years of experience as a machine learning engineer
    • Experience building and evaluating models for tabular classification problems
    • Experience building applications with LLM APIs
    • Experience with ML lifecycle tooling for training orchestration, experimentation, and model monitoring

    Key Skills:

    • Python
    • LightGBM/XGBoost/CatBoost
    • LLM APIs (e.g., OpenAI, Anthropic)
    • LangChain or LangGraph
    • Document and unstructured data processing (PDF/image extraction, text parsing)
    • Kubeflow, Airflow, MLflow
    • AI-powered developer tools (e.g., Claude Code, Cursor)

    Qualification:

    • Bachelor’s degree in a related field (or equivalent practical experience)

    Role Focus:

    • Develop AI systems that automate dispute and chargeback handling
    • Build models that automate refunds
    • Build and maintain evidence extraction pipelines
    • Prototype new modeling ideas and drive best-performing approaches into production
    • Collaborate across Engineering, Servicing Operations, Product, and ML Platform

    Other:

    • Base pay range: $165,000 - $225,000 (CA, WA, NY, NJ, CT) or $146,000 - $206,000 (all other U.S. states)
    • Equity rewards
    • Monthly stipends for health, wellness and tech spending
    • 100% subsidized medical coverage, dental and vision for you and your dependents
    • Flexible Spending Wallets
    • Time off - competitive vacation and holiday schedules
    • ESPP - An employee stock purchase plan

    Prepare for this role

    Recommended resources to build the skills for this position. Sponsored.

    Python for Everybody Specialization

    Coursera

    Learn Python from scratch — variables, data structures, web scraping, and databases.

    Python 3 Programming Specialization

    Coursera

    Intermediate Python covering classes, inheritance, APIs, and data processing.

    Functions, Tools and Agents with LangChain

    Coursera

    Advanced LangChain covering function calling, tool use, and conversational agents.

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