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About the Role

Capital One is creating trustworthy and reliable AI systems to transform banking. We are committed to building world-class applied science and engineering teams to advance our industry-leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. You will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses.

Responsibilities

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.
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.
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.
Flex interpersonal skills to translate the complexity of work into tangible business goals.
Guide and mentor a team of applied scientists and their managers without being a direct people leader.
Act as an external leader representing Capital One in the research community, collaborating with prominent faculty members.

Requirements

PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 6 years of experience in Applied Research.
PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields.
LLM PhD focus on NLP or Masters with 10 years of industrial NLP research experience.
Core contributor to team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) or through continued pre-training, post training pipeline for alignment and reasoning, LLM optimizations, complex reasoning with multi-agentic LLMs.
Numerous publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization).
Has worked on 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 with common training optimization frameworks (deep speed, nemo).
Experience contributing to the team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) or through continued pre-training, post training pipeline for alignment and reasoning, LLM optimizations, complex reasoning with multi-agentic LLMs.
Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.
An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes.
Experience in delivering libraries, platform level code or solution level code to existing products.
A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.

Skills

Pytorch
AWS Ultraclusters
Huggingface
Lightning
VectorDBs
AI
ML
Deep Learning
NLP
Large Language Models (LLMs)
Self-supervised learning
Robustness
Explainability
Reinforcement Learning from Human Feedback (RLHF)
Open-source languages
Cloud computing platforms
Training optimization
Deep speed
Nemo

Location

Cambridge, MA
McLean, VA
New York, NY
San Francisco, CA
San Jose, CA

Work Type

Full-time

Experience Level

Distinguished Applied Researcher
4 years of experience in Applied Research
6 years of experience in Applied Research
10 years of industrial NLP research experience

Education Level

PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields
M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields
PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields
LLM PhD focus on NLP or Masters

Salary/Compensations

Cambridge, MA: $306,300 - $349,500
McLean, VA: $306,300 - $349,500
New York, NY: $334,100 - $381,300
San Francisco, CA: $334,100 - $381,300
San Jose, CA: $334,100 - $381,300

Benefits

Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.

About the Company

At Capital One, we’re building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit.

Equal Opportunity

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
Capital One promotes a drug-free workplace.
Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.