Senior 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 a Senior Engineering Manager to lead our ML Training & Serving team. This is a senior technical leadership role with company-wide impact. You will directly lead a team of platform engineers, including senior technical leaders, and combine strong people leadership with deep ML infrastructure judgment. In close partnership with senior ICs, you will shape the platform’s strategy and technical direction. What You'll Do - Own the technical strategy and roadmap for ML training & serving, covering large-scale model training, model deployment workflows, GPU infrastructure, and low-latency model serving at scale. - Lead and grow a team of platform engineers while remaining deeply engaged in technical strategy and architectural trade-offs in close partnership with senior ICs. - Continuously evolve ML training & serving infrastructure to stay ahead of the frontier — anticipating where AI and ML are heading and building the infrastructure that makes those capabilities possible at Affirm before they become urgent needs. This includes large-scale training and serving of transformer-based models, GPU compute, reinforcement learning, and whatever comes next. - Partner with ML modeling, product, and infrastructure leadership to ensure ML training & serving infrastructure accelerates Affirm's most critical ML initiatives. - Establish engineering excellence across the organization: reliability, observability, developer experience, and operational rigor. - Recruit, develop, and retain world-class platform engineers. What We Look For - 10+ years of industry experience in software and/or machine learning engineering, with significant hands-on software engineering experience, including 4+ years managing engineering teams. - Deep expertise in building and operating large-scale ML infrastructure, with substantial experience in one or more of model training systems, model serving, deployment workflows, or GPU infrastructure. - Strong understanding of ML data needs — training datasets, data quality, reproducibility, evaluation data, and how data shapes model behavior and platform design. - Fluency with modern ML: deep neural networks, transformer architectures, reinforcement learning, large-scale GPU training and serving. - Strong systems thinking — comfortable reasoning from low-level infrastructure decisions to broad architectural trade-offs. - Track record of building platforms that meaningfully accelerate the productivity and impact of ML teams. - Experience on the applied ML modeling side is a plus — understanding how models are built makes you a better platform builder. - Proven track record of recruiting, developing, and retaining high-performing engineers, including coaching senior ICs and creating opportunities for them to expand their technical leadership. - Experience navigating ambiguity and leading through organizational complexity. - Bachelor's degree in a technical field or equivalent practical experience. Pay Grade - R Equity Grade - 9 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company). CAN base pay range per year: $209,000 - $269,000 #LI-Remote Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities. We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include: - Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents - Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses - Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge - ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount We believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We a

12+ years of industry experience in software and/or machine learning engineering, with significant hands-on software engineering experience, including 4+ years managing engineering managers. Deep expertise in building and operating large-scale ML infrastructure — feature stores, model serving systems, training pipelines, or equivalent. Strong understanding of data — data pipelines, data quality, and how data shapes model behavior and platform design. Fluency with modern ML: deep neural networks, transformer architectures, reinforcement learning, large-scale GPU training and serving. Strong systems thinking — comfortable reasoning from low-level infrastructure decisions to broad architectural trade-offs. Track record of building platforms that meaningfully accelerate the productivity and impact of ML teams. Experience on the applied ML modeling side is a plus — understanding how models are built makes you a better platform builder. Experience navigating ambiguity and leading through organizational complexity. Bachelor’s degree in a technical field or equivalent practical experience.