Machine Learning Engineer II (Servicing ML)

Affirm

Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $165,000–$225,000 / yr
Posted: 9 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $218k

This role $195k

$153k most similar roles pay here $277k

This role pays less than 72% of similar roles. Most pay $183,951–$251,375 — the shaded band above. At the midpoint, this role pays about $195k versus about $218k for comparable roles.

Based on 239 similar postings.

Employer

About Affirm

Affirm is a buy-now, pay-later (BNPL) financial technology company that offers point-of-sale installment loans to consumers, allowing them to split purchases into fixed monthly payments with transparent terms. Industry: Financial Technology & Consumer Lending

Affirm currently has 31 open roles on FindRole.

Listed pay typically runs $207,500–$265,000 across 30 roles with salary data.

Most-posted roles

View all roles at Affirm

At a glance

TL;DR · Machine Learning Engineer II (Servicing ML)

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Join the Servicing ML team as a Machine Learning Engineer II and help automate customer operations such as disputes, returns, fraud, and chargebacks using AI systems. You will develop models for refunds, build evidence extraction pipelines from unstructured data with LLM APIs like OpenAI or Anthropic, and collaborate across teams to drive solutions into production while ensuring robust monitoring and risk controls. The role requires 2+ years of experience in machine learning engineering, strong Python skills, proficiency in tools such as Kubeflow, Airflow, MLflow, and familiarity with document processing techniques for unstructured data.

Skills

Python LightGBM XGBoost CatBoost OpenAI LangChain Kubeflow Airflow MLflow LLM APIs PDF/image extraction Text parsing CI/CD

What you'll do

Develop AI systems to automate dispute and chargeback handling using structured evidence.
Build models to expedite refunds, ensuring faster returns of funds to customers.
Construct and maintain pipelines for processing unstructured data into actionable outputs.
Prototype new modeling ideas and drive high-performing approaches into production.
Collaborate with cross-functional teams to define requirements and communicate results effectively.

What we're looking for

2+ years of experience as a machine learning engineer.
Strong Python skills and production-quality code writing ability.
Experience with tabular classification models (LightGBM, XGBoost).
Proficiency in building applications using LLM APIs like OpenAI or Anthropic.
Familiarity with document processing and unstructured data handling.
Expertise in ML lifecycle tooling for training, experimentation, and monitoring.

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