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About the Role

Capital One is creating trustworthy and reliable AI systems to transform banking. This role involves partnering with cross-functional teams to deliver AI-powered products, leveraging a broad stack of technologies to analyze data, and building AI foundation models through all phases of development. You will engage in high-impact applied research to push AI developments into the next generation of customer experiences and translate complex work into tangible business goals.

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.
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 interpersonal skills to translate the complexity of work into tangible business goals.

Requirements

Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 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 5 years of industrial NLP research experience
Multiple publications 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)
Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens)
Publications in deep learning theory
Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR
PhD focused on topics related to optimizing training of very large deep learning models
Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression
Experience optimizing training for a 10B+ model
Deep knowledge of deep learning algorithmic and/or optimizer design
Experience with compiler design
PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning)
Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance
Experience deploying a fine-tuned large language model

Skills

AI
Machine Learning
Pytorch
AWS Ultraclusters
Huggingface
Lightning
VectorDBs
Deep learning
NLP
Model Sparsification
Quantization
Training Parallelism/Partitioning Design
Gradient Checkpointing
Model Compression
Compiler design
Transfer learning
Model adaptation
Model guidance

Location

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

Work Type

Full-time

Experience Level

Applied Researcher I

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 plus 2 years of experience in Applied Research
PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields

Salary/Compensations

Cambridge, MA: $218,700 - $249,600
McLean, VA: $218,700 - $249,600
New York, NY: $238,600 - $272,300
San Francisco, CA: $238,600 - $272,300
San Jose, CA: $238,600 - $272,300

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 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.
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.
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, 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.