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Senior Manager, ML Platform

Affirm

Remote · Canada Full-time Senior Yesterday

About the role

About

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 at Affirm.

This 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.

Who you are

  • 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

What the job involves

  • 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

Benefits

  • Compensation: We have a simple, flexible, and transparent remote-first compensation structure so you can make the best decisions for yourself and your family
  • Spending Wallets: Access tech, food, lifestyle, and family planning wallets for your expenses
  • Supportive Communities: Get involved with our employee resource groups and community groups
  • Remote-first Workforce: If your role is remote, you can set up shop anywhere in your home country
  • Generous Time Off: Take the time you need when life happens
  • Health Benefits: Get a plan that fits your needs
  • Mental Healthcare: Take care of your mind with great mental health programs
  • Parental Leave: Birth and non-birth parents get 18 weeks’ paid leave. Plus, a 4-week return-to-work transition program, at full base pay
  • Away Days: We offer 20 company-wide paid days off—which help our teams collectively pause to recharge
  • Learning & Development: Engage in exciting learning programs to level up your growth

Skills

AIdeep neural networksdistributed systemsGPUlarge-scale trainingmachine learningML infrastructuremodel servingplatform engineeringreinforcement learningtransformer architectures

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