Capital One National Association
Senior Manager, Data Science - LLM Customization Team
Capital One National Association, New York, New York, us, 10261
Overview
Senior Manager, Data Science - LLM Customization Team. At Capital One, we are a high-tech company using AI to transform financial services. You will help shape how AI transforms financial services and build production systems that utilize the latest generative AI technologies. Team Description
AI Foundations LLM Customization team is at the center of bringing our vision for LLMs and GenAI at Capital One to life. Our work touches every aspect of the research life cycle, from research to building production systems. We work with product, technology and business leaders to apply state-of-the-art AI to our business. You will drive experimentation, innovation, and next-generation experiences powered by generative AI. In this role, you will
Partner with a cross-functional team of data scientists, applied researchers, 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, Hugging Face, AWS Ultraclusters, LangChain, VectorDBs, and more — to reveal insights within large volumes of numeric and textual data. Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for business-specific applications and features. Build NLP models through all phases of development, from design through training, evaluation, and validation; partner with engineering teams to operationalize them in scalable and resilient production systems. Translate complex work into tangible business goals using strong interpersonal communication. The Ideal Candidate is
Innovative. You continually research and evaluate emerging technologies and apply state-of-the-art methods and applications. Creative. You thrive on solving big, undefined problems and sharing new ideas. Technical. You are comfortable with advanced ML and DL technologies, have hands-on experience with LLMs, and work with open-source tools and cloud platforms. Influential. You can lead cross-functional teams in breakthrough innovations and communicate findings to non-technical audiences. Experienced in training language models or large computer vision models with expertise in subdomains such as training optimization, self-supervised learning, explainability, or RLHF. Engineering-minded with a track record of delivering models at scale in training data and inference, and experience delivering libraries or platform-level code to products. Basic Qualifications
Currently has, or is in the process of obtaining, one of the following with the expectation that the degree will be obtained by the start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related field) plus 7 years of data analytics experience; A Master's Degree in a quantitative field or MBA with a quantitative concentration plus 5 years of data analytics experience; A PhD in a quantitative field plus 2 years of data analytics experience. At least 2 years of experience leveraging open-source programming languages for large-scale data analysis At least 2 years of experience working with machine learning At least 2 years of experience utilizing relational databases Preferred Qualifications
PhD in STEM field plus 4 years of data analytics experience At least 1 year of experience working with AWS At least 1 year of experience managing people At least 5 years’ experience in Python, Scala, or R for large-scale data analysis At least 5 years’ experience with machine learning LLM focus areas: NLP or Masters with 5 years of industrial NLP research experience; publications on pre-training of large language models; experience training a large language model from scratch; publications in deep learning theory; publications at ACL/NAACL/EMNLP, NeurIPS, ICML, or ICLR; and related fine-tuning topics such as supervised fine-tuning, instruction-tuning, dialogue-finetuning, or transfer learning. Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries are location-based and provided for candidates hired to work within specific locations. Salaries for part-time roles will be prorated. This role may be eligible for performance-based incentives, including cash bonuses and long-term incentives. Capital One offers a comprehensive benefits package. Eligibility varies based on status and employment type. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination and a drug-free workplace. For accommodations during the application process, contact Capital One Recruiting. See Capital One Careers website for more information.
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Senior Manager, Data Science - LLM Customization Team. At Capital One, we are a high-tech company using AI to transform financial services. You will help shape how AI transforms financial services and build production systems that utilize the latest generative AI technologies. Team Description
AI Foundations LLM Customization team is at the center of bringing our vision for LLMs and GenAI at Capital One to life. Our work touches every aspect of the research life cycle, from research to building production systems. We work with product, technology and business leaders to apply state-of-the-art AI to our business. You will drive experimentation, innovation, and next-generation experiences powered by generative AI. In this role, you will
Partner with a cross-functional team of data scientists, applied researchers, 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, Hugging Face, AWS Ultraclusters, LangChain, VectorDBs, and more — to reveal insights within large volumes of numeric and textual data. Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for business-specific applications and features. Build NLP models through all phases of development, from design through training, evaluation, and validation; partner with engineering teams to operationalize them in scalable and resilient production systems. Translate complex work into tangible business goals using strong interpersonal communication. The Ideal Candidate is
Innovative. You continually research and evaluate emerging technologies and apply state-of-the-art methods and applications. Creative. You thrive on solving big, undefined problems and sharing new ideas. Technical. You are comfortable with advanced ML and DL technologies, have hands-on experience with LLMs, and work with open-source tools and cloud platforms. Influential. You can lead cross-functional teams in breakthrough innovations and communicate findings to non-technical audiences. Experienced in training language models or large computer vision models with expertise in subdomains such as training optimization, self-supervised learning, explainability, or RLHF. Engineering-minded with a track record of delivering models at scale in training data and inference, and experience delivering libraries or platform-level code to products. Basic Qualifications
Currently has, or is in the process of obtaining, one of the following with the expectation that the degree will be obtained by the start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related field) plus 7 years of data analytics experience; A Master's Degree in a quantitative field or MBA with a quantitative concentration plus 5 years of data analytics experience; A PhD in a quantitative field plus 2 years of data analytics experience. At least 2 years of experience leveraging open-source programming languages for large-scale data analysis At least 2 years of experience working with machine learning At least 2 years of experience utilizing relational databases Preferred Qualifications
PhD in STEM field plus 4 years of data analytics experience At least 1 year of experience working with AWS At least 1 year of experience managing people At least 5 years’ experience in Python, Scala, or R for large-scale data analysis At least 5 years’ experience with machine learning LLM focus areas: NLP or Masters with 5 years of industrial NLP research experience; publications on pre-training of large language models; experience training a large language model from scratch; publications in deep learning theory; publications at ACL/NAACL/EMNLP, NeurIPS, ICML, or ICLR; and related fine-tuning topics such as supervised fine-tuning, instruction-tuning, dialogue-finetuning, or transfer learning. Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries are location-based and provided for candidates hired to work within specific locations. Salaries for part-time roles will be prorated. This role may be eligible for performance-based incentives, including cash bonuses and long-term incentives. Capital One offers a comprehensive benefits package. Eligibility varies based on status and employment type. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination and a drug-free workplace. For accommodations during the application process, contact Capital One Recruiting. See Capital One Careers website for more information.
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