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. You will directly lead a team of platform engineers and combine effective people leadership with strong technical judgment in ML infrastructure. Working closely with senior ICs and partners across Machine Learning and Infrastructure, you will help shape the team’s roadmap, drive execution, and ensure the platform reliably supports Affirm’s ML priorities.

What You'll Do

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.

What We Look For

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 work