Applied Researcher 4

Capital One • McLean, VA

3d

About The Position

Capital One’s AI Foundations team develops trustworthy and reliable AI systems, spanning the research life cycle from academic partnerships through production systems. The Applied Researcher 4 partners with product, technology, and business leaders to apply state-of-the-art AI and deliver AI-powered products that improve how customers interact with their money.

The role builds AI foundation models from design through training, evaluation, validation, and implementation, and conducts applied research to bring emerging AI developments into customer experiences. It also involves translating technical work into business goals and collaborating with senior researchers on internal technical reports or conference submissions. The position emphasizes research ownership, engineering at scale, high-quality machine learning contributions, and collaboration across data science, software engineering, machine learning engineering, and product teams.

The role is based on a full-time salary range that varies by location: $218,700–$249,600 in Cambridge, MA or McLean, VA, and $238,600–$272,300 in New York, NY or San Jose, CA. It is also eligible for performance-based incentive compensation, potentially including cash bonuses and/or long-term incentives. Capital One offers health, financial, and other benefits; eligibility varies by employment status and management level. Capital One will consider sponsoring a new qualified applicant for employment authorization.

Requirements

• Currently have or be in the process of obtaining a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or a related field, with the required degree obtained by the scheduled start date; alternatively, have an M.S. in one of these fields or a related field plus 2 years of experience in Applied Research.
• Have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
• Have a deep understanding of the foundations of AI methodologies.
• Have experience building large deep learning models in areas such as language, images, events, or graphs, and expertise in at least one of training optimization, self-supervised learning, robustness, explainability, or RLHF.
• Demonstrate an engineering mindset and a track record of delivering models at scale in training data and inference volumes.
• Have experience delivering libraries, platform-level code, or solution-level code to existing products.
• Demonstrate a track record of producing high-quality machine learning ideas or improving existing ideas, through accomplishments such as first-author publications or projects.
• Be able to select impactful research problems and independently pursue long-running research projects.

Nice To Haves

• PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering, or a related field.
• PhD focus on behavioral models or geometric deep learning, including graph neural networks, sequential models, or multivariate time series.
• Multiple papers on training models on graph and sequential data structures at KDD, ICML, NeurIPS, or ICLR.
• Experience scaling graph models to more than 50 million nodes.
• Experience with large-scale deep-learning-based recommender systems.
• Experience with production real-time and streaming environments.
• Contributions to open-source frameworks such as PyTorch Geometric or DGL.
• Proposed new methods for inference or representation learning on graphs or sequences.
• Experience working with datasets of more than 100 million users.
• Ability to reproduce and extend peer-reviewed AI research using modern open-source frameworks.
• Experience designing controlled experiments and documenting reproducibility results for internal or public research.

Responsibilities

• Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products.
• Use technologies including PyTorch, AWS Ultraclusters, Hugging Face, and Lightning to analyze large volumes of numeric and textual data.
• Build AI foundation models through design, training, evaluation, validation, and implementation.
• Conduct applied research that brings current AI developments into new customer experiences.
• Translate complex technical work into tangible business goals.
• Collaborate with senior researchers to prepare internal technical reports or conference submissions describing novel methods or findings.
• Own and pursue a research agenda, including selecting impactful research problems and carrying out long-running projects.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree