Capital One
Overview
At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading 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 are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description
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 work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, 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. 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. The Ideal Candidate
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 high quality 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. Basic Qualifications
Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or MS in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research Preferred Qualifications
PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models Member of team that has trained a large language model from scratch (10B+ parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, NeurIPS, ICML or ICLR Optimization (Training & Inference) PhD focused on optimizing training of very large deep learning models Experience with model sparsification, quantization, training parallelism/partitioning design, gradient checkpointing, model compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model The minimum and maximum full-time annual salaries for this role are listed below, by location. Salaries for part-time roles will be prorated. This information is for candidates hired to perform work within listed locations. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. This role is also eligible to earn performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI). Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with applicable laws and regulations regarding criminal background inquiries. If you require an accommodation during the application process, please contact Capital One Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com. Note
For technical support or questions about Capital One's recruiting process, please email Careers@capitalone.com. Capital One does not provide, endorse nor guarantee third-party products or services.
#J-18808-Ljbffr
At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading 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 are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description
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 work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, 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. 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. The Ideal Candidate
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 high quality 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. Basic Qualifications
Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or MS in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research Preferred Qualifications
PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models Member of team that has trained a large language model from scratch (10B+ parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, NeurIPS, ICML or ICLR Optimization (Training & Inference) PhD focused on optimizing training of very large deep learning models Experience with model sparsification, quantization, training parallelism/partitioning design, gradient checkpointing, model compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model The minimum and maximum full-time annual salaries for this role are listed below, by location. Salaries for part-time roles will be prorated. This information is for candidates hired to perform work within listed locations. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. This role is also eligible to earn performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI). Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with applicable laws and regulations regarding criminal background inquiries. If you require an accommodation during the application process, please contact Capital One Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com. Note
For technical support or questions about Capital One's recruiting process, please email Careers@capitalone.com. Capital One does not provide, endorse nor guarantee third-party products or services.
#J-18808-Ljbffr