Sr Distinguished Applied Researcher (World Models)

• 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.

• 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 new 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.

• Partner with a cross-functional team of scientists machine learning engineers software engineers and product managers to deliver AI-powered platforms and solutions that change how customers interact with their money.

• 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.

• 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.

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

• PhD in Electrical Engineering Computer Engineering Computer Science AI Mathematics or related fields plus 6 years of experience in Applied Research or M.S. in Electrical Engineering Computer Engineering Computer Science AI Mathematics or related fields plus 8 years of experience in Applied Research

• PhD in Computer Science Machine Learning Computer Engineering Applied Mathematics Electrical Engineering or related fields
• Behavioral Models
  
  • 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 at KDD ICML NeurIPs ICLR
  • 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)
  • Proposed new methods for inference or representation learning on graphs or sequences
  • Worked datasets with 100m+ users

What We Do

At Capital One we think and work like a tech company using our digital fluency to transform everything about the customer experience. We’re bending data to our will and turning a stodgy industry on its head. That’s reflected in our ranking as the number one business technology innovator in the U.S. in the 2016 InformationWeek Elite 100.

Why Work With Us

Here’s another question: What are you looking for? A place where curiosity is the starting point? Where data leads to human insights? Where humanity drives product development? We’re bringing breakthrough products and services to consumers small businesses and commercial clients. And each new idea makes life better for millions of people.

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