Affirm

Procurement

• Manage the pipeline of procurement requests and ensure that all stakeholder teams conduct timely review and approval
• Guide internal stakeholders through the process of submitting purchase requests and occasionally submit requests on behalf of business teams
• Manage vendor onboarding in our P2P system, collecting supplier details for proper review
• Conduct beginning to end process in contract review in partnership with Vendor Legal
• Manage internal events and hotel purchase process
• Manage all Affirm Poland purchases in partnership with Financial Partnerships
• Lead and implement assigned process improvement projects that will impact Procurement and broader teams at Affirm

Procurement Lead

Engineering Manager

• 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.

Senior Manager, Software Engineering – ML Platform

Machine Learning Engineer

• You will lead development of new fraud prediction models using a mix of approaches for tabular, graph, and behavioral data
• You will build and scale feature pipelines and training datasets from proprietary and third-party signals, partnering with data and platform teams when needed.
• You will prototype new modeling ideas and features, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
• You productionize models: integrate into batch and/or real-time decision systems, and improve reliability, latency, and operational robustness.
• You will instrument and monitor model and data health, and help define retraining/backtesting workflows as fraud patterns evolve.
• Identify and implement foundational improvements to how the team builds models.
• You will collaborate across Engineering, Fraud Analytics, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non-technical audiences.

Senior Manager, Machine Learning Engineering

Product Manager

• Deeply understand our customers and agents—what they need, what they expect, and where they struggle—through research, data, and constant iteration.
• Champion operational excellence—work closely with our Servicing and Operations teams to streamline workflows, reduce complexity, and unlock new levels of productivity.
• Design for scale through AI and automation—identify high-leverage areas where intelligent automation can boost agent efficiency and reduce contact volume, and assist with build-vs-buy evaluations for AI tooling that enhances customer and agent experiences.
• Drive an ambitious, thoughtful roadmap—identify impactful opportunities, prioritize ruthlessly, and guide execution from concept to launch and beyond.
• Translate insights into strategy—define a clear product vision informed by market trends, competitive analysis, behavioral data, and frontline feedback.
• Instrument and measure the right things—define metrics that matter, set clear success criteria, and use experimentation to drive performance improvements.
• Build for the long game—design scalable systems that can support a growing business, new contact channels, and ever-increasing expectations for speed and quality.
• Collaborate across the org—partner deeply with Engineering, Design, Analytics, Ops, Legal, Compliance, Risk, and senior leaders to drive aligned, cross-functional progress.
• Own ambiguity and unlock innovation—navigate tradeoffs, bring clarity to chaos, and lead with conviction in a fast-paced, constantly evolving environment.

Procurement Lead

Senior Manager, Software Engineering – ML Platform

Senior Manager, Machine Learning Engineering

Senior Manager, Machine Learning Engineering

Senior Product Manager, Card Servicing