Capital One
Sr Distinguished Applied Researcher (World Models)
Capital One, San Francisco, California, United States, 94199
Sr Distinguished Applied Researcher (World Models)
Overview
At Capital One, we are creating trustworthy and reliable AI systems to transform banking. Our AI & ML applications power real‑time, intelligent customer experiences—from flagging unusual charges to answering questions instantly. We are committed to building world‑class applied science and engineering teams that deliver breakthrough product experiences and scalable, high‑performance AI infrastructure. This role helps bring emerging AI capabilities to reimagine how we serve our customers and businesses.
Team Description The AI Foundations team is at the center of bringing our vision for AI to life. Our work spans the entire research life cycle, from partnering with academia to building production systems. We collaborate with product, technology, and business leaders to apply state‑of‑the‑art AI to our business. This individual‑contributor role drives strategic direction, partners with applied science, engineering, and product leaders, and represents Capital One in the research community with prominent faculty and industry partners.
Responsibilities
Partner with cross‑functional teams of data scientists, software engineers, ML engineers, and product managers to deliver AI‑powered products that change how customers interact with their money.
Leverage a broad stack of technologies—including PyTorch, AWS clusters, Hugging Face, Lightning, and VectorDBs—to extract insights from large volumes of numeric and textual data.
Build AI foundation models through all phases of development: design, training, evaluation, validation, and deployment.
Conduct high‑impact applied research to advance the latest AI developments and integrate them into customer experiences.
Translate technical work into tangible business goals, communicating complexity with clear impact statements.
Basic Qualifications
PhD in Electrical/Electronic Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related field, with 6+ years of experience in applied research (or MS in a related field with 8+ years).
Demonstrated expertise in developing AI foundation models using open‑source tools and cloud platforms.
Deep understanding of AI methodology foundations and the ability to build and scale large deep learning models.
Experience in training optimization, self‑supervised learning, robustness, explainability, or RLHF.
Track record of delivering models at scale for training data and inference volumes.
Proven ability to own and advance research agendas, including publishing first‑author papers or high‑impact projects.
Preferred Qualifications
PhD in Computer Science, Machine Learning, Applied Mathematics, Electrical Engineering, or related field.
Background in geometric deep learning (graph neural networks, sequential models, multivariate time series).
Leadership experience deploying large‑scale user‑behavior models and scaling graph models to >50M nodes.
Experience with real‑time, streaming production environments.
Contributions to open‑source frameworks such as PyTorch‑Geometric or DGL.
Strong research portfolio with papers at KDD, ICML, NeurIPS, ICLR.
Proven ability to propose new inference or representation learning methods for graphs or sequences.
Salary and Benefits Competitive total compensation of $311,900–$427,200, varying by location. Salary ranges reference the most competitive range for each city (e.g., Cambridge, MA; New York, NY). The role includes performance‑based incentive compensation, cash bonuses, and long‑term incentives.
Equal Opportunity Employer Capital One is an equal‑opportunity employer (EOE, including disability/veterans) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace. The company considers qualified applicants with a criminal history in a manner consistent with applicable laws. If you require accommodations, please contact Recruiting Accommodation at recruitingaccommodation@capitalone.com.
Technical Support and Contact For technical support or questions about the recruiting process, email Careers@capitalone.com. All information provided will be kept confidential and used only as required to provide reasonable accommodations.
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Team Description The AI Foundations team is at the center of bringing our vision for AI to life. Our work spans the entire research life cycle, from partnering with academia to building production systems. We collaborate with product, technology, and business leaders to apply state‑of‑the‑art AI to our business. This individual‑contributor role drives strategic direction, partners with applied science, engineering, and product leaders, and represents Capital One in the research community with prominent faculty and industry partners.
Responsibilities
Partner with cross‑functional teams of data scientists, software engineers, ML engineers, and product managers to deliver AI‑powered products that change how customers interact with their money.
Leverage a broad stack of technologies—including PyTorch, AWS clusters, Hugging Face, Lightning, and VectorDBs—to extract insights from large volumes of numeric and textual data.
Build AI foundation models through all phases of development: design, training, evaluation, validation, and deployment.
Conduct high‑impact applied research to advance the latest AI developments and integrate them into customer experiences.
Translate technical work into tangible business goals, communicating complexity with clear impact statements.
Basic Qualifications
PhD in Electrical/Electronic Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related field, with 6+ years of experience in applied research (or MS in a related field with 8+ years).
Demonstrated expertise in developing AI foundation models using open‑source tools and cloud platforms.
Deep understanding of AI methodology foundations and the ability to build and scale large deep learning models.
Experience in training optimization, self‑supervised learning, robustness, explainability, or RLHF.
Track record of delivering models at scale for training data and inference volumes.
Proven ability to own and advance research agendas, including publishing first‑author papers or high‑impact projects.
Preferred Qualifications
PhD in Computer Science, Machine Learning, Applied Mathematics, Electrical Engineering, or related field.
Background in geometric deep learning (graph neural networks, sequential models, multivariate time series).
Leadership experience deploying large‑scale user‑behavior models and scaling graph models to >50M nodes.
Experience with real‑time, streaming production environments.
Contributions to open‑source frameworks such as PyTorch‑Geometric or DGL.
Strong research portfolio with papers at KDD, ICML, NeurIPS, ICLR.
Proven ability to propose new inference or representation learning methods for graphs or sequences.
Salary and Benefits Competitive total compensation of $311,900–$427,200, varying by location. Salary ranges reference the most competitive range for each city (e.g., Cambridge, MA; New York, NY). The role includes performance‑based incentive compensation, cash bonuses, and long‑term incentives.
Equal Opportunity Employer Capital One is an equal‑opportunity employer (EOE, including disability/veterans) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace. The company considers qualified applicants with a criminal history in a manner consistent with applicable laws. If you require accommodations, please contact Recruiting Accommodation at recruitingaccommodation@capitalone.com.
Technical Support and Contact For technical support or questions about the recruiting process, email Careers@capitalone.com. All information provided will be kept confidential and used only as required to provide reasonable accommodations.
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