Machine Learning Engineer II

About the role

Join the Servicing ML team at Affirm, where you will play a crucial role in developing and refining machine learning systems aimed at enhancing customer service operations. Your work will focus on automating essential processes such as dispute resolution, returns, and fraud detection, ultimately improving the overall experience for both the company and its users.

Key facts

What you'll do

• Design and implement AI systems to automate the management of disputes and chargebacks, leveraging business logic and evidence to streamline operations.
• Create models that facilitate quicker customer refunds, ensuring a experience for users.
• Develop and sustain data extraction pipelines that handle unstructured data, employing large language model (LLM) workflows to derive actionable insights.
• Experiment with new modeling techniques, perform offline assessments, and successfully transition effective strategies into production while managing associated risks.
• Collaborate with cross-functional teams, including Engineering, Servicing Operations, Product, and ML Platform, to identify project requirements, evaluate trade-offs, and effectively communicate results to varied audiences.
• Engage in code reviews and provide constructive feedback to peers, fostering a culture of continuous improvement within the team.
• AI-assisted development tools to enhance coding efficiency and quality, ensuring and maintainable code.
• Stay updated on industry trends and advancements in machine learning, actively seeking opportunities for personal and professional development.

Requirements

• At least 2 years of hands-on experience working as a machine learning engineer.
• Strong proficiency in Python, with a track record of writing production-ready code.
• Experience in building and assessing models for tabular classification, particularly using gradient-boosted decision trees like LightGBM, XGBoost, or CatBoost.
• Familiarity with developing applications that LLM APIs, including structured data extraction and prompt engineering, along with experience using orchestration frameworks such as LangChain or LangGraph.
• Knowledge of processing unstructured data, including document handling, PDF/image extraction, and text parsing techniques.
• Experience with machine learning lifecycle management tools for training, experimentation, and model oversight, such as Kubeflow, Airflow, or MLflow.
• Ability to translate complex business challenges into functional solutions that incorporate multiple software components, while writing clear, well-tested, and adaptable code.
• Comfort with navigating extensive codebases, debugging existing code, and providing valuable feedback during code reviews.
• Demonstrated initiative in seeking feedback and pursuing growth opportunities in both personal and professional contexts.
• Excellent written and verbal communication skills to facilitate effective collaboration with a globally distributed engineering team.
• A Bachelor's degree in a relevant field or equivalent practical experience is required.

Nice to have

• Experience with document processing and unstructured data handling, including PDF/image extraction and text parsing techniques.
• Familiarity with cloud-based machine learning services and platforms.
• Knowledge of advanced machine learning algorithms and techniques beyond standard practices.

Skills & tools

• Proficient in Python programming
• Familiar with LightGBM, XGBoost, CatBoost for model building
• Experience with OpenAI and Anthropic APIs
• Knowledge of LangChain and LangGraph for orchestration
• Familiarity with Kubeflow, Airflow, and MLflow for managing ML workflows
• Experience with AI-assisted development tools like Claude Code and Cursor

Practical notes

• Base Pay Grade: L
• Equity Grade: 6
• Salary range for the USA (CA, WA, NY, NJ, CT): $165,000 - $225,000 annually
• Salary range for the USA (all other states): $146,000 - $206,000 annually
• Total compensation package includes base salary, equity, monthly stipends for health, wellness, and technology expenses, along with comprehensive benefits.
• Benefits include full medical coverage for employees and dependents, dental, and vision insurance.
• Affirm operates as a remote-first organization, allowing employees to work from nearly any location within the country of employment.
• The company provides competitive benefits such as fully subsidized health insurance premiums, flexible spending accounts, generous paid time off, and an employee stock purchase plan.
• Reasonable accommodations will be made available for candidates with disabilities throughout the hiring process.
• For positions in Los Angeles or San Francisco, Affirm will consider applicants with arrest and conviction records in accordance with local laws.
• By applying, candidates acknowledge that they have read Affirm's Global Candidate Privacy Notice and consent to the processing of their personal information as outlined.