Capital One currently has 293 active AI-related job listings. The majority of these roles are focused on serving infrastructure, accounting for 28% of the total, followed closely by agents at 26% and post-training at 23%. Engineering is the dominant function, with 234 roles, and hiring is primarily concentrated in the United States. Frequent tech tags include model_serving, vector_db, and llm_observability, suggesting a focus on the operational aspects of AI deployment. In the last 30 days, Capital One posted 124 new AI roles, representing a 22% increase compared to the previous 30-day period.
Currently tracking 241 active AI roles, down 26% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $123k–$392k (avg $231k).
Capital One currently has 305 active AI-related roles in our index. The most common open titles are: Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) (9), Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) (8), Applied Researcher I (6), Distinguished Engineer (6), Applied Researcher II (5). Most positions are in Engineering and Research.
Capital One's active AI hiring is concentrated in: serving infrastructure (28%), agents (27%), post-training (23%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Capital One is hiring AI talent in: United States (299 roles), United Kingdom (3 roles), Canada (2 roles), Philippines (1 role).
Job postings at Capital One most frequently reference: model serving, vector db, fine tuning, llm observability, inference infra.
In the past 30 days, Capital One has posted 96 new AI-related roles. That is a -26% change versus the prior 30 days (130 → 96).
| Title | Stage | AI score |
|---|---|---|
| Manager, Data Scientist - Recommendation & Personalization Systems Manager, Data Scientist focused on Recommendation & Personalization Systems within an Applied AI team. The role involves architecting and deploying personalized recommendation engines using Foundation Models, Reinforcement Learning, and Transformer-based architectures. It operates at the intersection of research and real-world impact, dealing with high-scale ML models and billions of customer records in the fintech domain. | AgentPost-train | 7 |
| Sr. Distinguished Engineer Senior Distinguished Engineer role focused on technical leadership for productionizing machine learning applications and systems at scale within the financial services industry. The role involves driving the creation and evolution of ML models and software, leveraging cloud architectures, optimizing data pipelines, and mentoring engineers. Requires extensive experience in data-intensive solutions and the ML development lifecycle. |
| ShipServe |
| 7 |
| Senior Associate, Data Scientist - Model Risk Office This role is in Capital One's Model Risk Office, focusing on identifying and quantifying risks associated with models, including Generative AI. The Senior Associate Data Scientist will build machine learning models to challenge existing production models, contribute to model governance, and validate models across various business domains. They will leverage technologies like PyTorch, Hugging Face, LangChain, Vector Databases, and LLMOps to analyze multi-modal data and present findings to executives. | ShipAgent | 7 |
| Manager, Data Scientist - Model Risk Office This role is within Capital One's Model Risk Office, focusing on identifying and quantifying risks associated with models, including Generative AI. The Data Scientist will build machine learning models to challenge existing production models and contribute to the model governance framework. They will validate models across various business domains and present findings to executives. The role requires experience with ML, data analysis, and databases, with a preference for GenAI and model validation experience. | ShipPost-train | 7 |