Applied Researcher I (AI Foundations)

AIToolboard; McLean (VA); On-site; USD 120,000 - 190,000; Full time

Job summary

Capital One is seeking an Applied Researcher I (AI Foundations) to join our AI Foundations team. The role focuses on building trustworthy AI systems and delivering AI-powered customer experiences in collaboration with data scientists, software engineers, ML engineers and product managers.

You will work with PyTorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more to develop foundation models, train and evaluate them, and translate research into scalable production capabilities

Qualifications

• Currently pursuing or has a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics or related field, with degree by start date or MS with 2 years applied research experience.
• Experience with large language models, NLP or ML research preferred.
• Strong publication record or project contributions in ML.

Responsibilities

• Collaborate with a cross-functional team of data scientists, software engineers, ML engineers and product managers to deliver AI-powered products.
• Develop AI foundation models from design through training, evaluation, validation and deployment.
• Translate research outcomes into scalable, customer-facing features.
• Engage in applied research to push AI developments into production systems.
• Communicate technical concepts to non-technical stakeholders.

Skills

Analytical thinking

Open-source

Cloud computing

Leadership

Education

PhD in CS, EE, CE, AI or related

MS + 2 years Applied Research

Tools

PyTorch

AWS Ultraclusters

Huggingface

VectorDBs

Job description

Jobs / Applied Researcher I (AI Foundations)

Applied Researcher I (AI Foundations)

Full-time and Part-time

About the Role

Applied Researcher I (AI Foundations)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 are bringing 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. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.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.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, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
• Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
• Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
• Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands‑on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
• Has a deep understanding of the foundations of AI methodologies.
• Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF.
• 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 high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
• Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.

Basic Qualifications:

• 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.

Preferred Qualifications:

• 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
• O