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 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.
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 |
|---|---|---|
| Applied Researcher II (AI Foundations, LLM Core and Agentic AI) Applied Researcher II focused on AI Foundations, LLM Core, and Agentic AI at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like PyTorch and VectorDBs. Responsibilities include building AI foundation models through all development phases (design, training, evaluation, validation, implementation) and conducting high-impact applied research to advance customer experiences. The ideal candidate has a deep understanding of AI methodologies, experience building large deep learning models (language, images, events, graphs), expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF, and a track record of delivering models at scale. A PhD or MS with significant experience is required, with a focus on NLP, geometric deep learning, or optimization. | PretrainAgent |
| 9 |
| Applied Researcher II (AI Foundations) Applied Researcher II (AI Foundations) at Capital One, focusing on building AI foundation models from design through training, evaluation, validation, and implementation. The role involves applied research to develop next-generation customer experiences and requires experience with large deep learning models, training optimization, and delivering models at scale. The position is research-oriented within the fintech domain. | PretrainPost-train | 9 |
| Applied Researcher II (AI Foundations) Applied Researcher II focused on AI Foundations at Capital One, working on building AI foundation models from design through training, evaluation, validation, and implementation. The role involves applied research to integrate AI developments into customer experiences and requires experience with large deep learning models, training optimization, and delivering models at scale. Collaboration with cross-functional teams and a strong understanding of AI methodologies are key. | PretrainPost-train | 9 |
| Applied Researcher I (AI Foundations) Applied Researcher I (AI Foundations) at Capital One, focusing on building AI foundation models from design through training, evaluation, validation, and implementation. The role involves applied research to push AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires a PhD or MS with experience in AI/ML, deep learning, and delivering models at scale, with a strong understanding of AI methodologies and experience in training optimization, self-supervised learning, robustness, explainability, or RLHF. | PretrainPost-train | 9 |
| Distinguished Applied Researcher Distinguished Applied Researcher role focused on building AI foundation models from design through training, evaluation, validation, and implementation, and engaging in high-impact applied research to develop next-generation customer experiences. The role involves partnering with cross-functional teams and leveraging technologies like PyTorch, AWS, Huggingface, and VectorDBs. Requires a PhD or MS with significant experience in applied research, with a focus on large deep learning models, training optimization, self-supervised learning, robustness, explainability, or RLHF. Experience training large language models from scratch or through continued pre-training is highly preferred. | PretrainPost-train | 9 |
| Applied Researcher I (AI Foundations, LLM Core and Agentic AI) Applied Researcher I role focused on AI Foundations, LLM Core, and Agentic AI at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch and VectorDBs, and building AI foundation models through all development phases. It emphasizes applied research to advance customer experiences and requires a deep understanding of AI methodologies, experience building large deep learning models, and a track record of delivering models at scale. | PretrainPost-train | 9 |
| Applied Researcher II (AI Foundations) Applied Researcher II focused on AI Foundations at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch and VectorDBs. Responsibilities include building AI foundation models through all development phases (design, training, evaluation, validation, implementation) and conducting applied research to integrate AI advancements into customer experiences. The ideal candidate has a deep understanding of AI methodologies, experience building large deep learning models, and a track record of delivering models at scale. | PretrainPost-train | 8 |
| Applied Researcher II (AI Foundations) Applied Researcher II focused on AI Foundations at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch and VectorDBs. Responsibilities include building AI foundation models through all development phases (design, training, evaluation, validation, implementation) and conducting applied research to integrate AI advancements into customer experiences. Requires a deep understanding of AI methodologies, experience building large deep learning models (language, images, events, graphs), and expertise in areas like training optimization, self-supervised learning, robustness, explainability, or RLHF. A track record of delivering models at scale and contributing to research through publications or projects is essential. | PretrainPost-train | 8 |
| Applied Researcher I (AI Foundations) Applied Researcher focused on building AI foundation models from design through training, evaluation, validation, and implementation. The role involves applied research to push AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires experience building large deep learning models and delivering models at scale. | PretrainPost-train | 8 |
| Senior Manager, Data Science - Quantum Computing Research This role is for a Senior Manager of Data Science focused on Quantum Computing Research within financial services. The candidate will define and execute a research roadmap, conduct research in quantum optimization and quantum machine learning, collaborate with hardware vendors, publish findings, and identify business applications. The role emphasizes leadership, innovation, and a deep understanding of quantum information science, with a focus on translating research into tangible solutions. | Pretrain | 7 |
| Senior Manager, Data Science - Quantum Computing Research (Remote-Eligible) This role is for a Senior Manager of Data Science focused on Quantum Computing Research within financial services. The candidate will define and execute a research roadmap for quantum algorithms and applications, collaborate with hardware vendors, and publish findings. The role emphasizes exploring the intersection of quantum computing and AI for financial challenges. | Pretrain | 7 |