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Salary: CAD 181,000 - 241,000 / annual
Affirm is seeking an Engineering Manager to lead the ML Training & Serving platform team. You will directly manage a team of platform engineers, combining strong people leadership with deep technical judgment in ML infrastructure. The role spans model training, deployment workflows, GPU infrastructure, and low-latency model serving.
Key responsibilities include: partnering with senior ICs and engineering leadership to define and execute the ML infrastructure roadmap; leading, coaching, and growing platform engineers while staying technically engaged; driving delivery and operational health across reliability, developer experience, performance, and cost; evaluating and adopting modern ML infrastructure capabilities including transformer-based workloads and GPU compute; collaborating with ML modeling, product, and infrastructure teams to support Affirm's highest-priority ML initiatives; and recruiting, developing, and retaining high-performing platform engineers.
Required qualifications: 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 production experience building and operating ML or distributed systems infrastructure, with hands-on expertise 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 ability to partner on architectural trade-offs. Track record of delivering platforms or infrastructure that improve engineering or ML team productivity. Experience recruiting, coaching, and developing engineers across career stages. Effective cross-functional collaboration and ability to lead through ambiguity. Bachelor's degree in a technical field or equivalent practical experience. Applied ML modeling experience is a plus.
