Engineering Manager, Machine Learning Platform

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. We are seeking an Engineering Manager to lead our ML Training & Serving team, combining effective people leadership with strong technical judgment in ML infrastructure. The role involves shaping the team’s roadmap, driving execution, and ensuring the platform supports Affirm’s ML priorities.

Responsibilities:

• Partner with senior ICs and engineering leadership to define and execute the roadmap for ML training & serving, spanning model training, deployment workflows, GPU infrastructure, and low-latency model serving
• Lead, coach, and grow a team of platform engineers while staying closely engaged in technical decisions and execution
• Drive delivery and operational health for the team’s infrastructure, balancing reliability, developer experience, performance, and cost
• Evaluate and adopt modern ML infrastructure capabilities as Affirm’s needs evolve, including transformer-based workloads and GPU compute
• Collaborate with ML modeling, product, and infrastructure teams to ensure the platform supports Affirm’s highest-priority ML initiatives
• Recruit, develop, and retain high-performing platform engineers

Requirements:

• 7+ years of industry experience in software and/or machine learning engineering, including 2+ years managing engineers and meaningful hands-on software engineering experience
• Strong experience building and operating production ML or distributed systems infrastructure, with hands-on experience in at least one of model training, model serving, deployment workflows, or GPU infrastructure
• Solid understanding of ML data needs, including training datasets, data quality, reproducibility, and evaluation data
• Familiarity with modern ML workloads, such as deep learning, transformer architectures, and large-scale training or serving
• Strong systems thinking and the ability to partner with senior ICs on architectural trade-offs
• Track record of delivering platforms or infrastructure that improve the productivity and impact of engineering or ML teams
• Experience recruiting, coaching, and developing engineers across career stages
• Effective cross-functional collaboration and the ability to lead through ambiguity
• Bachelor's degree in a technical field or equivalent practical experience
• Experience with applied ML modeling is a plus