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 - Credit Line Increase Program Capital One is seeking a Manager, Data Scientist to lead the development and deployment of machine learning models for their Credit Line Increase Program. This role involves partnering with cross-functional teams, leveraging technologies like Python and AWS, and managing the full model lifecycle from design to implementation and monitoring. The ideal candidate has a strong statistical background, experience with various ML techniques, and a customer-centric approach. | Post-train | 7 |
| Principal Data Scientist Capital One's DataLabs AML team is modernizing money laundering detection using advanced analytics, statistics, and machine learning models. This Principal Data Scientist role involves end-to-end development, deployment, and monitoring of risk management models, partnering cross-functionally, and defending these systems to regulators. The role requires strong ML/statistical skills, experience with Python/R, and SQL, with a focus on building and validating predictive models in the financial services domain. |
| Post-train |
| 7 |
| Principal Associate, Data Scientist - AI for Data Data Scientist role focused on developing AI-enabled features across the data lifecycle within a fintech company. Responsibilities include building ML models through all phases, leveraging technologies like Python, AWS, and Spark, and collaborating with cross-functional teams. Requires experience with various ML techniques, deep learning frameworks, and NLP/IR/Search/Recommendations/Fine-tuning on LLMs. | Post-trainServe | 7 |
| Senior Manager, Data Science - Cash Flow Underwriting Senior Manager, Data Science for Cash Flow Underwriting at Capital One. This role focuses on leveraging advanced machine learning techniques to build and implement predictive models for risk and usage, transforming raw banking data into valuable features for forecasting creditworthiness and customer behavior. The role involves leading a team, strategic planning, and end-to-end model development. | Post-train | 7 |
| Principal Associate, Data Scientist - Cash Flow Underwriting Data Scientist role focused on building machine learning models for cash flow underwriting in the fintech domain. The role involves transforming raw banking data into predictive features to forecast creditworthiness and customer behavior, covering all phases of model development from design to implementation. | Post-train | 7 |
| Senior Associate, Data Scientist - Cash Flow Underwriting This role focuses on leveraging advanced machine learning techniques to identify and engineer predictive signals from cash flow and transaction data for risk and usage models in the fintech domain. The data scientist will transform raw banking data into high-value features to forecast creditworthiness and customer behavior, building ML models through all phases of development. | Data | 7 |
| Principal Associate, Data Scientist - Financial Services Data Scientist role focused on building machine learning models for financial services applications like customer lifetime valuation, product recommendation, and fraud detection, with a specific mention of Generative AI. The role involves the full ML lifecycle from design to implementation and requires experience with Python, SQL, AWS, and various ML techniques. | ShipPost-train | 7 |
| Principal Associate, Data Scientist - US Card (Generative AI Systems) This role is for a Principal Associate Data Scientist on the Generative AI Systems (Genesis) team within Capital One's Card Data Science division. The team builds state-of-the-art generative AI solutions for various applications including dialogue, text summarization, reading comprehension, speech recognition, image/document processing, and time-series sequencing. The role involves partnering with cross-functional teams to deliver customer-facing and internal applications, leveraging technologies like Python, AWS, and Spark, and building machine learning models through all phases of development. The ideal candidate is customer-focused, innovative, creative, technically proficient, statistically-minded, and adept at handling large datasets. | ShipPost-train | 7 |
| Sr Lead Machine Learning Engineer This role focuses on the engineering aspects of machine learning, specifically in productionizing ML applications and systems at scale within a financial services context. The engineer will be involved in the design, development, implementation, and maintenance of ML models and infrastructure, ensuring high availability and performance. The role emphasizes collaboration, code quality, and leveraging cloud platforms for ML deployment. | Serve | 7 |
| Director, Data Scientist - US Card (Mainstreet Acquisitions) Capital One is seeking a Director, Data Scientist to lead efforts in transforming how next-generation models are built and trained for the US Card business. This role involves leveraging machine learning and AI techniques to innovate credit forecasting, working with a cross-functional team, and managing the full lifecycle of model development from design through implementation. The position requires a strong quantitative background, experience in data analytics, machine learning, and relational databases, with a focus on innovation and leadership. | Post-train | 7 |
| Senior Associate, Data Science - Consumer Credit Risk Models and Data This role focuses on deploying, optimizing, and modernizing machine learning model pipelines and execution platforms for consumer credit risk management within a fintech company. The primary responsibility is to ensure these models are effectively implemented and provide insights for strategic decision-making, including loss allowances, stress testing, and capital allocation. | Serve | 7 |
| Sr. Distinguished Machine Learning Engineer Senior Distinguished Machine Learning Engineer role focused on technical leadership for productionizing ML 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 other engineers. Requires extensive experience in data-intensive solutions, ML development lifecycle, and programming. | ShipServe | 7 |
| Manager, Data Scientist - Model Risk Office Manager of Data Scientists within the Model Risk Office, focusing on validating and building statistical or machine learning models, including those with unique risks associated with Generative AI. The role involves partnering with cross-functional teams, leveraging technologies like Python and AWS, and translating complex work into business goals. The ideal candidate is creative, a leader, statistically-minded, and a data guru. | ShipPost-train | 7 |
| Senior Manager, Data Science - Model Risk Office Senior Manager role focused on Model Risk Office within Capital One, leading teams to identify and quantify risks associated with models, challenge production models, and contribute to model governance. The role involves leveraging data science, machine learning, and various technologies to ensure better decision-making and defend against model failures in a financial services context. | ShipPost-train | 7 |
| Principal Associate, Data Scientist - Mainstreet Acquisitions Capital One is seeking a Principal Associate, Data Scientist for their Mainstreet Acquisitions team. This role involves developing and deploying valuation models for credit underwriting, leveraging alternative data sources and advanced modeling techniques. The position requires building machine learning models through all phases of development, from design through training, evaluation, validation, and implementation, using technologies like Python, AWS, and Spark. The ideal candidate is customer-focused, innovative, creative, technically proficient, statistically-minded, and skilled in handling large datasets. | Post-train | 7 |
| Manager, Data Scientist - Card Intelligence Model Risk Management Manager, Data Scientist role focused on Card Intelligence Model Risk Management within Capital One's fintech domain. The role involves building machine learning models through all phases of development, including design, training, evaluation, validation, and implementation. It requires partnering with cross-functional teams and leveraging technologies like Python, AWS, H2O, and Spark. The position emphasizes statistical modeling, data analysis, and understanding customer data to drive data-driven decision-making. Experience in model governance and end-to-end development is preferred. | Post-train | 7 |
| 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 |
| Manager, Data Scientist - Emerging Payments & Airkey Manager, Data Scientist role at Capital One focused on Emerging Payments & Airkey. The team builds ML models for customer-facing payment experiences, processing large-scale financial data using technologies like XGBoost, transformers, embeddings, and LLMs. The role involves building ML models from design through production for millions of customers, partnering with cross-functional teams, and leveraging various technologies like SQL, Python, AWS, and Spark. | ShipPost-train | 7 |
| Lead Data Scientist - Deep Learning Practitioner Lead Data Scientist role focused on developing and deploying deep learning models for underwriting and supporting LLM-based product development in a fintech company. | Post-trainServe | 7 |