Sr. Distinguished Applied Researcher

Overview At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real‑time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML bring humanity and simplicity to banking. We are committed to building world‑class applied science and engineering teams and continue our industry‑leading capabilities with breakthrough product experiences and scalable, high‑performance AI infrastructure. Team Description The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. Role Summary In this role, you will: Partner with a cross‑functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI‑powered products that change how customers interact with their money. Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high‑impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate You love the process of analyzing and creating, and share our passion to do the right thing for our customers. Innovative: you continually research and evaluate emerging technologies, staying current on state‑of‑the‑art methods and seeking opportunities to apply them. Creative: you thrive on bringing definition to big, undefined problems and are not afraid to share new ideas. A leader: you challenge conventional thinking, work with stakeholders to improve the status quo, and are passionate about talent development for your own team and beyond. Technical: you are comfortable with open‑source languages, have hands‑on experience developing AI foundation models, and are passionate about further development. Deep understanding of AI methodologies and experience building large deep learning models on language, images, events, or graphs. Expertise in training optimization, self‑supervised learning, robustness, explainability, or RLHF. Engineering mindset with a track record of delivering models at scale in both training data and inference volumes. Experience delivering libraries or platform‑level code to existing products. Proven track record of new ideas or improvements in machine learning, evidenced by publications or projects. Ability to own and pursue an independent research agenda, choosing impactful research problems and carrying out long‑running projects autonomously. Basic Qualifications PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related field plus 6 years of applied research experience, OR M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related field plus 8 years of applied research experience. Preferred Qualifications PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, or related field. LLM: PhD focus on NLP or Masters with 10 years of industrial NLP research experience. Core contributor to a team that has trained a large language model from scratch (10B+ parameters, 500B+ tokens). Numerous publications at ACL, NAACL, EMNLP, NeurIPS, ICML or ICLR on topics related to large language model pre‑training. Experience with an LLM (open source or commercial) that is currently available for use. Demonstrated ability to guide the technical direction of a large‑scale model training team. Experience working with 500+ node GPU clusters and scaling models to 70B parameters and 1T+ tokens. Experience with common training optimization frameworks (DeepSpeed, Nemo). Compensation The minimum and maximum full‑time annual salaries for this role are listed below, by location. Sales Territory: $311,900 - $356,000 Cambridge, MA: $343,100 - $391,600 McLean, VA: $343,100 - $391,600 New York, NY: $374,300 - $427,200 San Francisco, CA: $374,300 - $427,200 Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. Salary and incentive compensation offer will be reflected in the candidate’s offer letter. Eligible applicants may also receive performance‑based incentive compensation, including cash bonus and/or long‑term incentives. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level. Legal Capital One is an equal‑opportunity employer (EOE, including disability/veteran) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace and confirms that it will consider qualified applicants with a criminal history in a manner consistent with applicable laws. We do not accept agency applications. This role is expected to accept applications for a minimum of five business days. Contact If you require an accommodation, please contact Capital One Recruiting at View phone number on click.appcast.io or via email at View email address on click.appcast.io. For technical support or questions about Capital One’s recruiting process, please send an email to View email address on click.appcast.io. All information you provide will be kept confidential and used only as required to provide needed reasonable accommodations. Capital One does not provide, endorse, nor guarantee and is not liable for third‑party products, services, educational tools or other information available through this site. Capital One Financial is composed of several entities. Positions posted in Canada are for Capital One Canada, in the United Kingdom for Capital One Europe, and in the Philippines for Capital One Philippines Service Corp. (COPSSC). #J-18808-Ljbffr