Applied Researcher II
Not Disclosed•Full-TimeOn-site
location_onNYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States
About the Mission
At Capital One, we are creating trustworthy and reliable AI systems to change banking for good. For years, we have led the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions instantly, our applications of AI & ML bring humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams to reimagine how we serve the customers and businesses that love our products.
About the Team
The AI Foundations team sits 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 collaborate closely with product, technology, and business leaders to apply state-of-the-art AI to our business challenges.
The Role
In this role, you will partner with a cross-functional team of data scientists, software engineers, and product managers to deliver AI-powered products that transform how customers interact with their money. You will leverage a broad stack of technologies to reveal insights hidden within huge volumes of numeric and textual data, building AI foundation models through all phases of development from design to implementation.
You will engage in high-impact applied research to push the latest AI developments into the next generation of customer experiences. A key part of your day involves flexing your interpersonal skills to translate the complexity of your work into tangible business goals. We are looking for individuals who love the process of analyzing and creating, share a passion for doing the right thing, and understand that the end goal is making the right decision for our customers.
Hiring Process
This role is expected to accept applications for a minimum of 5 business days. Please note that no agencies are accepted for this position. If you require an accommodation during the recruiting process, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com.
Equal Opportunity & Culture
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. We promote a drug-free workplace and will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws. We are committed to building a diverse and inclusive environment where talent can thrive.
Work location
Work model: On-site
NYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States
New York, New York
Key Responsibilities
- check_circlePartner with cross-functional teams to deliver AI-powered products
- check_circleBuild AI foundation models through design, training, evaluation, and implementation
- check_circleTranslate complex technical work into tangible business goals
- check_circleLeverage technologies like PyTorch and AWS to extract insights from large data volumes
- check_circleConduct high-impact applied research to advance customer experiences
Requirements
- verifiedPhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research
- verifiedM.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research
- verifiedExperience building large deep learning models
- verifiedExperience delivering libraries, platform level code or solution level code
- verifiedTrack record of first author publications or projects in machine learning
- verifiedWork authorization sponsorship available
Nice to Have
PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, or Electrical Engineering. LLM focus on NLP or Masters with 5 years of industrial NLP research experience, multiple publications on pre-training of large language models (e.g., technical reports, SSL techniques, optimization), membership in a team that trained a large language model from scratch (10B+ parameters, 500B+ tokens), publications in deep learning theory, or publications at ACL, NAACL, EMNLP, Neurips, ICML, or ICLR. Behavioral Models focus on geometric deep learning (Graph Neural Networks, Sequential Models, 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 greater than 50m nodes, experience with large-scale deep learning-based recommender systems, experience with production real-time and streaming environments, contributions to open source frameworks (pytorch-geometric, DGL), proposed new methods for inference or representation learning on graphs or sequences, or experience with datasets having 100m+ users. Optimization focus on topics related to optimizing training of very large deep learning models, multiple years of experience and/or publications on model sparsification, quantization, training parallelism/partitioning design, gradient checkpointing, or model compression, experience optimizing training for a 10B+ model, deep knowledge of deep learning algorithmic and/or optimizer design, or experience with compiler design. Finetuning focus on guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning), demonstrated knowledge of transfer learning, model adaptation, and model guidance, or experience deploying a fine-tuned large language model. Data Preparation publications studying tokenization, data quality, dataset curation, or labeling, contribution to a major open source corpus, or contribution to open source libraries for data quality, dataset curation, or labeling.
Benefits & Perks
check_circleEligible for performance-based incentive compensation including cash bonuses and/or long-term incentivescheck_circleComprehensive, competitive, and inclusive set of health, financial, and other benefits
Similar Job Opportunities
Skills, education and keywords
Skills: Machine Learning, Ai, Pytorch, Aws, Huggingface, Lightning, Vector DBS, Deep Learning, LLM, NLP.
Education: PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields required; Master's in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields with 4 years experience.
Frequently asked questions about Applied Researcher II at Capital One
What does a Applied Researcher II at Capital One do?expand_more
In this Applied Researcher II at Capital One role, you will partner with cross-functional teams to deliver ai-powered products; build ai foundation models through design, training, evaluation, and implementation; translate complex technical work into tangible business goals; and leverage technologies like pytorch and aws to extract insights from large data volumes.
What are the requirements for this Applied Researcher II role?expand_more
Capital One is looking for candidates who meet the following requirements: PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research; M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research; Experience building large deep learning models; Experience delivering libraries, platform level code or solution level code; Track record of first author publications or projects in machine learning; and Work authorization sponsorship available.
Where is the Applied Researcher II role at Capital One located?expand_more
Applied Researcher II at Capital One is based in NYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States. This is a on-site role.
Is this Applied Researcher II job remote, hybrid, or on-site?expand_more
Capital One has listed this Applied Researcher II role as on-site.
How much experience is required for this Applied Researcher II role?expand_more
Applied Researcher II at Capital One typically requires 2–4 years of relevant experience at the senior level.
What skills do you need for the Applied Researcher II role at Capital One?expand_more
Key skills for Applied Researcher II at Capital One include Machine Learning; Ai; Pytorch; Aws; Huggingface; Lightning; Vector DBS; and Deep Learning.
What education is required for Applied Researcher II at Capital One?expand_more
Educational requirements for this role: PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields required; and Master's in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields with 4 years experience.
What category does the Applied Researcher II role belong to?expand_more
Applied Researcher II at Capital One is part of the it job category on Recrutus.