Stripe
Fintech · Payments
- HQ
- San Francisco, US
- Founded
- 2010
- Size
- 8,000+
- Website
- stripe.com
- Blog
- stripe.com
Products
Fintech · Payments
Stripe currently has 40 active job listings related to AI. The majority of these roles, 63%, are focused on agents. Engineering is the primary function for these hires, with the United States and Canada being the top hiring countries. Frequent tech tags include agent orchestration, LLM observability, and tool use. Over the last 30 days, Stripe has added 14 new AI roles, representing a 40% increase compared to the previous 30-day period.
Stripe currently has 43 active AI-related roles in our index. The most common open titles are: Product Manager, Ecosystem Risk (3), Forward Deployed AI Accelerator, Marketing (2), AI Engineer, Accounting Technical Solutions Lead, Backend Engineer, AI Security. Most positions are in Engineering and Product.
Stripe's active AI hiring is concentrated in: agents (58%), application (19%), data (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Stripe is hiring AI talent in: United States (25 roles), Canada (13 roles), United Kingdom (2 roles), India (2 roles).
Job postings at Stripe most frequently mention: Production ML Systems, Cybersecurity ML, System Design, Software Engineering, Product Management.
In the past 30 days, Stripe has posted 19 new AI-related roles. That is a +73% change versus the prior 30 days (11 → 19).
Currently tracking 25 active AI roles, up 46% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $151k–$220k (avg $185k).
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Engineer Stripe's Applied ML team is looking for an ML Engineer to help reform user interaction with their financial platform. This role involves automating tasks and assisting users by leveraging and fine-tuning LLMs, taking projects from ideation through to production deployment. The engineer will analyze opportunities, train and evaluate models, run experiments, and deploy solutions, contributing to ML architecture and the broader ML community. | ShipPost-train | 8 |
| Data Scientist, Fraud Data Scientist role focused on building and improving machine learning models for fraud detection and loss management systems within Stripe's financial infrastructure. The role involves working with supervised and unsupervised ML, statistical modeling, causal inference, and experimentation, with a strong emphasis on moving models from research to production and driving measurable impact on financial integrity and user trust. Experience with fraud/risk/financial crimes and deploying models in production is required. | ShipData | 7 |
| Machine Learning Engineering Manager - Fraud Detection Machine Learning Engineering Manager for Fraud Detection at Stripe. The role involves leading a team of engineers to build and improve ML systems for fraud detection, focusing on merchant experience and financial ecosystem safety. Responsibilities include team leadership, recruiting, cross-functional execution, and strategic direction for risk management. | Ship | 7 |
| Machine Learning Engineer, Capital Underwriting Machine Learning Engineer for Stripe Capital, focusing on designing, building, training, evaluating, and deploying ML models for underwriting and portfolio management. The role involves working with large-scale datasets, productionizing models, and collaborating with cross-functional teams to provide financing opportunities while meeting financial performance and regulatory goals. | Ship | 7 |