
location_onNYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States
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 in real time, our applications of AI & ML bring humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams to continue our industry-leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.
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. We collaborate with product, technology, and business leaders to apply the state of the art in AI to our business.
As an Applied Researcher II, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses. You will 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.
In this role, you will leverage a broad stack of technologies to reveal insights hidden within huge volumes of numeric and textual data. You will build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Your work involves engaging in high-impact applied research to take the latest AI developments and push them into the next generation of customer experiences. You will flex your interpersonal skills to translate the complexity of your work into tangible business goals.
The ideal candidate loves the process of analyzing and creating while sharing a passion for doing the right thing. You will be innovative, continually researching and evaluating emerging technologies to stay current on state-of-the-art methods. You will be creative, thriving on bringing definition to big, undefined problems and pushing hard to find answers. As a leader, you will challenge conventional thinking and work with stakeholders to identify and improve the status quo, while remaining passionate about talent development.
Candidates hired to work in other locations will be subject to the pay range associated with that location. This role is expected to accept applications for a minimum of 5 business days. No agencies please.
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes 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 regarding criminal background inquiries.
If you require an accommodation to apply for a position, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information provided will be kept confidential and used only to the extent required to provide needed reasonable accommodations.
Skills: Machine Learning, Ai, Pytorch, Aws, Huggingface, Lightning, Vectordbs, 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; PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering, or related fields preferred.
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
PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, or Electrical Engineering. LLM focus on NLP (PhD) 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, model pre-training optimization). Membership in a team that has trained a large language model from scratch (10B+ parameters, 500B+ tokens). Publications in deep learning theory. Publications at ACL, NAACL, EMNLP, Neurips, ICML, or ICLR. PhD focused on 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. Experience with compiler design. PhD focused on 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.
Capital One • New York, New York
Recrutus helps candidates discover roles that match their skills and helps teams reach qualified applicants faster. Browse by metro, discipline, or work style — from internships to senior leadership.