Machine Learning Engineer II

What you'll do

• You will develop AI systems that automate dispute and chargeback handling using structured evidence and business logic, creating a better experience for our customers.
• You will build models that automate refunds, getting money back to our customers faster.
• You will build and maintain evidence extraction pipelines that process unstructured data using LLM-powered workflows to produce structured, actionable outputs.
• You will prototype new modeling ideas, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
• You will collaborate across Engineering, Servicing Operations, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non-technical audiences.

What we look for

• You have a total of 2+ years of experience as a machine learning engineer
• Strong Python skills and experience writing production-quality code
• Experience building and evaluating models for tabular classification problems (preferably gradient-boosted decision trees like LightGBM/XGBoost/CatBoost).
• Experience building applications with LLM APIs (e.g., OpenAI, Anthropic), including structured extraction, prompt engineering, and orchestration frameworks like LangChain or LangGraph.
• Familiarity with document and unstructured data processing (PDF/image extraction, text parsing, or similar).
• Experience with ML lifecycle tooling for training orchestration, experimentation, and model monitoring (e.g., Kubeflow, Airflow, MLflow, or equivalent internal platforms).
• Proficient in using AI-powered developer tools (e.g., Claude Code, Cursor, or similar) to accelerate iteration, debugging, and code quality as part of day-to-day development workflows.
• You have mastered taking a simple problem or business scenario into a solution that interacts with multiple software components, and executing on it by writing clear, easily understood, well tested and extensible code.
• You are comfortable navigating a large code base, debugging others' code, and providing feedback to other engineers through code reviews.
• Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders.
• You have strong verbal and written communication skills that support effective collaboration with our global engineering team.