Affirm
Fintech · BNPL
- HQ
- San Francisco, US
- Founded
- 2012
- Website
- affirm.com
Affirm currently has 19 active job listings related to artificial intelligence. The majority of these roles are focused on serving infrastructure, accounting for 32% of the openings, followed closely by data, application, and agents, each representing 26% or 21% of the listings. Engineering is the primary function hiring for these positions, with the United States being the dominant hiring country. Key technical areas include model serving, inference infrastructure, and agent orchestration.
Currently tracking 11 active AI roles, down 32% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $124k–$310k (avg $233k).
Fintech · BNPL
Affirm currently has 27 active AI-related roles in our index. The most common open titles are: Machine Learning Engineer II (2), Manager, Machine Learning Engineering (Fraud) (2), Manager, Machine Learning Engineering (Underwriting) (2), Quantitative Analytics Lead (2), Senior Staff Machine Learning Engineer, (ML Underwriting) (2). Most positions are in Engineering and Product.
Affirm's active AI hiring is concentrated in: agents (30%), serving infrastructure (30%), application (19%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Affirm is hiring AI talent in: United States (24 roles), Canada (3 roles).
Job postings at Affirm most frequently reference: model serving, agent orchestration, inference infra, tool use, llm observability.
In the past 30 days, Affirm has posted 9 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Senior Manager, Software Engineering (ML Platform) Senior Manager to lead ML Platform engineering at Affirm, focusing on building and operating infrastructure for feature computation, model training, and model serving at scale. The role involves technical strategy, roadmap ownership, team leadership, and staying ahead of AI/ML trends. | ServeData | 8 |
| Senior Manager, Software Engineering, (ML Platform) Senior Manager to lead ML Platform engineering organization, building and operating critical infrastructure for ML capabilities at Affirm. Focus on real-time and batch feature computation, model training, and model serving at scale, including transformer-based models and GPU compute. | ServePost-train | 8 |
| Quantitative Analytics Lead This role focuses on the Model Risk Management (MRM) team within Affirm's Enterprise Risk & Internal Audit department. The primary responsibility is to perform independent challenges and ongoing monitoring of machine learning models used for credit underwriting, credit risk, and fraud detection. This involves identifying model weaknesses, collaborating with model owners for remediation, and partnering cross-functionally to maintain the MRM framework. The role also involves ensuring timely resolution of audit and regulatory requests. | Eval GatePost-train | 7 |
| Software Engineer II, Backend (ML Training & Serving) Software Engineer II to join the ML Training & Serving engineering team, responsible for building and operating critical infrastructure for training and serving ML models at Affirm. The role involves distributed systems, ML infrastructure, and platform engineering, focusing on reliability, developer velocity, and durable systems. | ServeData | 7 |
| Machine Learning Engineer II Machine Learning Engineer II at Affirm to build and improve AI systems for automating customer operations like disputes, returns, fraud, and chargebacks. Responsibilities include developing AI systems for dispute/chargeback handling, building models for automated refunds, creating evidence extraction pipelines using LLM-powered workflows, prototyping and deploying models, and collaborating with cross-functional teams. Requires 2+ years of ML engineering experience, strong Python, experience with tabular classification models, LLM APIs (OpenAI, Anthropic), prompt engineering, orchestration frameworks (LangChain, LangGraph), unstructured data processing, and ML lifecycle tooling. | AgentData | 7 |
| Machine Learning Engineer II Machine Learning Engineer II at Affirm to build and improve AI systems for automating customer operations like disputes, returns, fraud, and chargebacks. The role involves developing AI systems using LLM-powered workflows, building models for refunds, and creating evidence extraction pipelines. It requires experience in production ML, LLM APIs, and ML lifecycle tooling. | AgentData | 7 |
| Manager, Machine Learning Engineering (Underwriting) Manager of ML Engineers building an economic decisioning engine for underwriting in a fintech company, focusing on strategy, talent development, and cross-functional collaboration. | Ship | 7 |
| Manager, Machine Learning Engineering (Underwriting) Manager of ML Engineering for Affirm's underwriting group, focusing on building and scaling the economic decisioning engine using ML techniques for underwriting and optimizing applications. The role involves setting technical strategy, mentoring engineers, and collaborating with product and risk leaders. | Ship | 7 |
| Manager, Machine Learning Engineering (Fraud) Manager of Machine Learning Engineering focused on fraud detection in a fintech setting. The role involves leading a team to develop and deploy ML models for fraud prevention, covering the full ML lifecycle from feature development to production monitoring. Emphasis on advanced techniques like representation learning and transformers, and cross-functional collaboration. | Ship | 7 |
| Manager, Machine Learning Engineering (Fraud) Manager of Machine Learning Engineering for Fraud at Affirm, focusing on building and iterating on fraud detection models throughout the ML lifecycle, including advanced techniques like representation learning and transformers. The role involves setting strategy, leading a team, and cross-functional collaboration to integrate models into decisioning systems. | ShipPost-train | 7 |
| Senior Machine Learning Engineer (Fraud) Senior Machine Learning Engineer focused on building and improving real-time fraud prediction models for a fintech company. Responsibilities include developing new models, scaling feature pipelines, prototyping, productionizing models, and monitoring their health. Requires experience in ML model development, production deployment, and handling tabular/graph/behavioral data. | ServeData | 7 |
| Machine Learning Engineer II (Fraud) Machine Learning Engineer II focused on fraud detection at Affirm. This role involves developing and iterating on fraud prediction models, building and scaling feature pipelines, prototyping new modeling ideas, productionizing models into real-time decision systems, and monitoring model health. Requires experience with tabular data, gradient-boosted trees, deep learning frameworks, distributed data processing, and ML lifecycle tooling. | ServeData | 7 |
| Senior Staff Machine Learning Engineer, (ML Underwriting) Senior Staff ML Engineer at Affirm focused on ML Underwriting. This role involves defining and driving multi-year technical strategy for ML, leading the design, implementation, and scaling of advanced ML systems, and providing broad technical leadership across the ML organization. The engineer will mentor senior engineers, shape long-term modeling capabilities, and ensure operational excellence for critical ML systems. Experience with large-scale, real-time ML systems, end-to-end ML system design, Python, PyTorch, XGBoost, and distributed ML infrastructure is required. | ServePost-train | 7 |
| Senior Staff Machine Learning Engineer, (ML Underwriting) Senior Staff Machine Learning Engineer at Affirm, focusing on ML Underwriting. This role involves defining and driving multi-year technical strategy for ML, leading the design, implementation, and scaling of advanced ML systems, and providing technical leadership and mentorship. The position requires extensive experience in deploying and operating large-scale, real-time ML systems, with a focus on representation learning, embedding-based modeling, and sequence modeling. | Serve | 7 |
| Analyst II, Full Stack This role focuses on developing and optimizing fraud decisioning strategies within a fintech company. It involves extensive data analytics, collaborating with cross-functional teams (Product, Engineering, Operations, Finance), and developing new fraud features. A key responsibility is creating scalable frameworks for proprietary fraud machine learning models and evaluating data sources to mitigate fraud risk. The role also involves partnering with the Machine Learning team on fraud and identity verification strategies and owning the end-to-end analytics workflow, including defining metrics and creating dashboards. | Data | 7 |