Machine Learning Engineer II

About the Role

The Servicing ML team is central to Affirm's mission of making credit more honest and friendly. By leveraging machine learning and AI, the company aims to provide a more flexible and consumer-centric approach to buying now and paying later, without the pitfalls of hidden fees or compounding interest. As a member of this team, you will have the opportunity to work on complex problems that have a direct impact on customer experience and the company's overall success.

What You Will Do

• Develop AI systems that automate dispute and chargeback handling, utilizing structured evidence and business logic to create a better experience for customers.
• Build models that automate refunds, ensuring customers receive their money back more quickly.
• Design and maintain evidence extraction pipelines that process unstructured data using LLM-powered workflows, producing structured and actionable outputs.
• Prototype new modeling ideas, conduct offline experiments, and drive the best-performing approaches into production with appropriate risk controls in place.
• Collaborate across Engineering, Servicing Operations, Product, and ML Platform teams to define requirements, evaluate trade-offs, and communicate results clearly to both technical and non-technical audiences.
• Work on optimizing existing models and systems, ensuring they are running efficiently and effectively.
• Participate in the development of the team's technical roadmap, contributing to the growth and improvement of Affirm's machine learning capabilities.
• Engage in code reviews, providing feedback to other engineers and contributing to the overall quality of the codebase.
• Stay up-to-date with the latest developments in machine learning and AI, applying this knowledge to continuously improve Affirm's systems and processes.

What We Are Looking For

• A minimum of 2+ years of experience as a machine learning engineer, with a strong background in building and deploying models in production environments.
• Strong Python skills, with experience writing production-quality code and a keen eye for detail.
• Experience with building and evaluating models for tabular classification problems, preferably with gradient-boosted decision trees like LightGBM, XGBoost, or CatBoost.
• Familiarity with LLM APIs, such as OpenAI or Anthropic, and experience with building applications that utilize these technologies.
• Knowledge of document and unstructured data processing, including PDF/image extraction, text parsing, or similar technologies.
• Experience with ML lifecycle tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, Airflow, or MLflow.
• Proficiency in using AI-powered developer tools to accelerate iteration, debugging, and code quality.
• Ability to take ownership of growth, seeking feedback from team members, managers, and stakeholders to continuously improve skills and performance.
• Strong verbal and written communication skills, with the ability to collaborate effectively in a global engineering team environment.
• A Bachelor's degree in a related field or equivalent practical experience.

Nice to Have

• Experience with cloud-based technologies, such as AWS or Google Cloud, and containerization using Docker.
• Knowledge of agile development methodologies and version control systems like Git.
• Familiarity with data visualization tools, such as Tableau or Power BI, to effectively communicate insights to stakeholders.
• Experience with natural language processing (NLP) or computer vision, and their applications in real-world problems.

Benefits and Perks

• Competitive base salary, with opportunities for growth and professional development.
• Equity in the company, providing a sense of ownership and long-term investment in Affirm's success.
• Comprehensive health, dental, and vision insurance, with 100% subsidy for employees.
• Generous PTO and holiday policy, ensuring a healthy work-life balance.
• Remote work stipend, supporting the setup and maintenance of a productive home office environment.
• Access to the latest technologies and tools, staying at the forefront of machine learning and AI development.
• Opportunities for professional growth, including training, mentorship, and education support.

• Ensure your resume and online profiles highlight specific experience with machine learning and AI technologies, particularly in Python and LLM APIs.
• Prepare examples of models you've built and deployed, focusing on the challenges you faced and how you overcame them.
• Practice explaining complex technical concepts in simple terms, as effective communication with non-technical stakeholders is crucial.
• Research Affirm's approach to credit and payments, demonstrating your understanding of the company's mission and values during the interview process.
• Be ready to discuss your experience with collaboration tools and version control systems, highlighting your ability to work in a team environment.
• Consider creating a portfolio or GitHub repository showcasing your projects, providing a tangible representation of your skills and experience.