Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

Tailor your resume to this Applied Researcher 5 role.

Rezi rewrites your resume against Capital One's job description. Free.

Resume score gauge reading 58 out of 100

Don't guess if your resume is good enough.

See how it scores against the Applied Researcher 5 posting at Capital One — free, in seconds.

About the Role

Capital One is creating trustworthy and reliable AI systems to change banking for good. We are committed to building world-class applied science and engineering teams to advance AI/ML capabilities for innovative customer experiences and scalable AI infrastructure. You will help bring transformative 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.
Leverage a broad stack of technologies (Pytorch, AWS Ultraclusters, Huggingface, Lightning, etc.) to reveal insights from large volumes of 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 push the latest AI developments into next-generation customer experiences.
Translate the complexity of your work into tangible business goals.
Lead cross-functional research threads that bridge prototype model development and deployment with ML engineering partners.
Design and lead small-scale research initiatives, guiding junior researchers or engineers through experimental design and evaluation.

Requirements

Innovative mindset with continuous research and evaluation of emerging technologies and state-of-the-art methods.
Creative problem-solver who thrives on defining and solving big, undefined problems.
Leadership qualities, challenging conventional thinking and improving the status quo.
Technical proficiency with open-source languages and hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
Deep understanding of AI methodologies.
Experience building large deep learning models (language, images, events, or graphs).
Expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF.
Engineering mindset with a track record of delivering models at scale (training data and inference volumes).
Experience delivering libraries, platform-level code, or solution-level code to existing products.
Track record of high-quality ideas or improvements in machine learning, demonstrated by accomplishments such as first author publications or projects.
Ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.

Skills

Pytorch
AWS Ultraclusters
Huggingface
Lightning
AI
ML
Deep Learning
NLP
LLM
Geometric Deep Learning
Graph Neural Networks
Sequential Models
Multivariate Time Series
Recommender Systems
Optimization
Finetuning
Transfer Learning
Tokenization
Data Quality
Dataset Curation
Labeling

Location

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

Work Type

Full-time

Experience Level

Applied Research
5+ years industrial NLP research experience (preferred)

Education Level

PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields (or MS + 4 years experience)
PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields (preferred)
PhD focus on NLP or Masters with 5 years of industrial NLP research experience (preferred)
PhD focus on topics in geometric deep learning (preferred)
PhD focused on topics related to optimizing training of very large deep learning models (preferred)
PhD focused on topics related to guiding LLMs with further tasks (preferred)
Publications studying tokenization, data quality, dataset curation, or labeling (preferred)

Salary/Compensations

McLean, VA: $262,500 - $299,600
Cambridge, MA: $262,500 - $299,600
New York, NY: $286,400 - $326,800
San Francisco, CA: $286,400 - $326,800
San Jose, CA: $286,400 - $326,800

Benefits

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

About the Company

Capital One is creating trustworthy and reliable AI systems, changing banking for good.
We are leading the industry in using machine learning for real-time, intelligent, automated customer experiences.
Our applications of AI & ML bring humanity and simplicity to banking.
We are committed to building world-class applied science and engineering teams.
We aim to advance industry-leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.
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.

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.
If you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com.