Applied Researcher I (Multi-agent Systems, Knowledge Graphs/GraphRAG/Graph-of-Thought / GoT, MCP, LangGraph, Agent Protocols)

About the role

The AI Foundations – AI Software Engineering team builds scalable, state-of-the-art AI architectures designed to transform the software development lifecycle at Capital One. Our goal is to empower internal engineers by developing multi-agent solutions that streamline design, code generation, system migration, and troubleshooting to operate software more effectively at scale.

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

Requirements

• 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.
• Creative.
• A leader.
• Technical.

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 include:
• 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).
• Publishations in deep learning theory.
• Papers in ACL, NAACL and EMNLP, Neurips, ICML or ICLR.
• PhD focused on multi-agent systems, autonomous agents, planning, or reinforcement learning.
• Experience with techniques like tool-use integration, memory management for agents, or verifiable agent behavior.
• Knowledge Graph Research.
• PhD focused on knowledge representation and reasoning, graph neural networks (GNNs), or large-scale data integration.
• Publications in relevant venues (e.g., ISWC, WWW, KDD, Neurips, ICML) on knowledge graph construction, embedding, querying, or reasoning.
• Experience in designing, implementing, and deploying industrial-scale Knowledge Graph solutions.
• Demonstrated expertise with graph databases (e.g., Neo4j, JanusGraph) and graph embedding techniques.
• Finetuning.
• 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

• 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 include:
• 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).
• Publishations in deep learning theory.
• Papers in ACL, NAACL and EMNLP, Neurips, ICML or ICLR.
• PhD focused on multi-agent systems, autonomous agents, planning, or reinforcement learning.
• Experience with techniques like tool-use integration, memory management for agents, or verifiable agent behavior.
• Knowledge Graph Research.
• PhD focused on knowledge representation and reasoning, graph neural networks (GNNs), or large-scale data integration.
• Publishations in relevant venues (e.g., ISWC, WWW, KDD, Neurips, ICML) on knowledge graph construction, embedding, querying, or reasoning.
• Experience in designing, implementing, and deploying industrial-scale Knowledge Graph solutions.
• Demonstrated expertise with graph databases (e.g., Neo4j, JanusGraph) and graph embedding techniques.
• Finetuning.
• 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.

Benefits

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.

Pay

Salaries for this role are listed below, by location.

• Cambridge, MA: $218,700 - $249,600 for Applied Researcher I
• Mclean, VA: $218,700 - $249,600 for Applied Researcher I
• New York, NY: $238,600 - $272,300 for Applied Researcher I
• San Francisco, CA: $238,600 - $272,300 for Applied Researcher I
• San Jose, CA: $238,600 - $272,300 for Applied Researcher I

Schedule

This role is full-time.