Manager, Machine Learning Engineering (Portfolio ML)

About the Role

This role is for a Manager, Machine Learning Engineering within the Portfolio ML team, focusing on Offer Personalization. You will lead efforts to optimize loan opportunities, ensuring merchants offer the best financing programs and customers receive personalized offers, all while contributing to Affirm's mission of making credit more honest and friendly.

About the Team

The Portfolio ML team is crucial for managing and optimizing the flow of loan opportunities across Affirm's properties. We develop models, tools, and libraries to support portfolio management actions, balancing unit economics, product growth, and user experience. Our work powers ROA-based decisioning, real-time and offline conversion rate prediction, counterfactual portfolio simulation, and loan valuation, sitting within the Decisions Foundations organization.

Responsibilities

• Set the technical strategy for your team on a year-long timescale, aligning it with critical, business-impacting projects.
• Collaborate with product management, design, and analytics to ensure technical sustainability, manage risks, and understand trade-offs throughout the product development lifecycle.
• Act as a force-multiplier for your team by defining and advocating for robust technical solutions and operational processes.
• Own your team’s operations and availability, establishing monitoring, triage rotations, playbooks, policies, testing, and alerting for "keep the lights on" and on-call efforts.
• Foster a culture of quality and ownership by setting and advocating for code review and design standards through writing and tech talks.
• Develop talent within your team by providing feedback, guidance, and leading by example.

Requirements

• Bachelor's degree in a technical field with 8+ years of industry experience (relevant PhD can count for up to 2 years of experience).
• Proficiency in machine learning, including experience with Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration.
• Strong engineering skills in Python and data manipulation skills using SQL.
• Proven experience delivering major features, system components, or deprecating existing functionality through well-defined technical and execution plans.
• Ability to write high-quality code that is easily understood and utilized by others.
• Comfort thriving in ambiguity, capable of understanding systems from low-level language idioms to large-scale architecture.
• Demonstrated mastery in gathering and iterating on feedback from engineering and cross-functional peers.
• Strong verbal and written communication skills to support effective collaboration with a global engineering team.

Nice-to-Haves

• Domain knowledge in credit risk, portfolio management, learning to rank, and personalization.