[Hiring] Staff Applied Researcher @Capital One

Role Description

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. Our applications of AI & ML are bringing humanity and simplicity to banking.

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.

This is an individual contributor (IC) role driving strategic direction through collaboration with Applied Science, Engineering and Product leaders across Capital One. As a well-respected IC leader, you will guide and mentor a team of applied scientists and their managers without being a direct people leader.

You will be expected to be an external leader representing Capital One in the research community, collaborating with prominent faculty members in the relevant AI research community.

What You’ll Do

• 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, 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.
• Define and steward novel research directions that expand the organization’s long-term scientific agenda, ensuring foundational discoveries translate into deployable capabilities.

Qualifications

• You love the process of analyzing and creating, but also share our passion to do the right thing.
• Innovative. You continually research and evaluate emerging technologies.
• Creative. You thrive on bringing definition to big, undefined problems.
• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo.
• Technical. You’re comfortable with open-source languages and are passionate about developing further.
• Has a deep understanding of the foundations of AI methodologies.
• Experience building large deep learning models, whether on language, images, events, or graphs.
• An engineering mindset as shown by a track record of delivering models at scale.
• 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.
• Possess the ability to own and pursue a research agenda.

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 related fields plus 6 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 10 years of industrial NLP research experience.
• Core contributor to team that has trained a large language model from scratch (10B + parameters, 500B+ tokens).
• Numerous publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR on topics related to the pre-training of large language models.
• 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 working with 500+ node clusters of GPUs.
• Experience with common training optimization frameworks (deep speed, nemo).
• PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series).
• Member of technical leadership for model deployment for a very large user behavior model.
• Multiple papers on topics relevant to training models on graph and sequential data structures.
• Worked on scaling graph models to greater than 50m nodes.
• Experience with large scale deep learning based recommender systems.
• Experience with production real-time and streaming environments.
• Contributions to common open source frameworks (pytorch-geometric, DGL).
• Worked datasets with 100m+ users.
• PhD focused on topics related to optimizing training of very large language models.
• 5+ years of experience and/or publications on topics like Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression.
• PhD focused on topics related to guiding LLMs with further tasks.
• Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance.
• Experience deploying a fine-tuned large language model.
• Numerous Publications studying tokenization, data quality, dataset curation, or labeling.
• Leading contributions to one or more large open source corpus (1 Trillion + tokens).
• Core contributor to open source libraries for data quality, dataset curation, or labeling.
• Demonstrated history of initiating and leading multi-year research programs that shaped the direction of AI or ML subfields.

Benefits

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

Salary Information

• Cambridge, MA: $306,300 - $349,500 for Staff Applied Researcher.
• McLean, VA: $306,300 - $349,500 for Staff Applied Researcher.
• New York, NY: $334,100 - $381,300 for Staff Applied Researcher.
• San Francisco, CA: $334,100 - $381,300 for Staff Applied Researcher.
• San Jose, CA: $334,100 - $381,300 for Staff Applied Researcher.

Company Description

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.