PayPal currently has 26 active AI-related job listings. The majority of these roles, 46%, are focused on agents, with serving infrastructure and data roles also representing significant portions. Engineering is the primary function for these hires, with the United States being the dominant hiring country. Frequent tech tags include model_serving, agent_orchestration, and inference_infra. In the last 30 days, PayPal has posted 12 new AI roles, representing a 500% increase compared to the previous 30-day period.
Currently tracking 20 active AI roles, down 49% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $118k–$359k (avg $241k).
PayPal currently has 19 active AI-related roles in our index. The most common open titles are: Sr Machine Learning Engineer (6), Director, Director, ML Engineering & Agentic Systems, Director, Product Management, Lead Product Manager – Risk Decisioning Platform, Machine Learning Engineer. Most positions are in Engineering and Product.
PayPal's active AI hiring is concentrated in: agents (37%), application (26%), data (21%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
PayPal is hiring AI talent in: United States (16 roles), Ireland (3 roles).
Job postings at PayPal most frequently reference: model serving, agent orchestration, recommender systems, inference infra, tool use.
In the past 30 days, PayPal has posted 15 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Staff Machine Learning Engineer Staff Machine Learning Engineer at PayPal in Bengaluru, India, focused on developing and deploying advanced ML models, particularly in Generative AI and Agentic AI, with a strong emphasis on production readiness, fine-tuning, and evaluation within the fintech domain. | AgentPost-train | 8 |
| Director, Director, ML Engineering & Agentic Systems Director of ML Engineering & Agentic Systems at PayPal, focusing on leading teams to deliver LLM-based agentic systems and consumer-facing ML products at scale within the fintech domain. The role involves driving product and technical strategy, defining engineering health objectives, and building ML platform infrastructure. | Agent |
| 8 |
| Sr Machine Learning Engineer This role focuses on designing, developing, and implementing machine learning models and algorithms, with a strong emphasis on LLM agents and multi-agent systems. The engineer will build scalable ML pipelines, deploy models into production, and integrate them into products and services, requiring experience with agentic frameworks, LLM APIs, and evaluation methodologies. | AgentServe | 8 |
| Principal Engineer, Agentic Systems Principal Engineer role focused on building agentic systems, likely involving LLM-based agents, multi-agent orchestration, and tool-use frameworks within the fintech domain. The role emphasizes setting technology roadmaps, influencing senior executives, and mentoring engineers. | Agent | 7 |