Senior Manager, Software Engineering; ML 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.

Machine Learning is central to how affirm delivers on its mission — powering decisions across underwriting, fraud, servicing, and personalization. We are seeking a Senior Manager to lead our ML Platform engineering organization, the team that builds and operates the critical infrastructure enabling every ML capability s is a high‑impact, technically demanding role at the intersection of distributed systems, modern AI, and platform engineering.

You will manage a team of engineering managers and stay deeply connected to the engineers building the platform, ensuring we continuously evolve ahead of affirm's ML ambitions.

• Own the technical strategy and roadmap for ML Platform, covering real‑time and batch feature computation, model training infrastructure, and model serving at scale.
• Lead and grow a team of engineering managers, while staying hands‑on with the technical direction and maintaining close partnership with ICs.
• Continuously evolve the platform 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 the platform 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.

• 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.

Pay Grade - R

Equity Grade - 15

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 equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)

USA base pay range (CA, WA, NY, NJ, CT) per year: $260,000 - $310,000

USA base pay range (all other U.S. states) per year: $232,000 - $282,000

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.

• 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…