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. Translate the complexity of your work into tangible business goals. The Ideal Candidate
You love the process of analyzing and creating, and are committed to making the right decision for customers. Innovative. You continually research and evaluate emerging technologies and stay current on published state-of-the-art methods and applications. Creative. You thrive on defining big problems, asking questions, and sharing new ideas. A leader. You challenge conventional thinking and mentor others; you’re passionate about talent development. Technical. You are comfortable with open-source languages and have hands-on experience developing AI foundation models and solutions using open-source tools and cloud platforms. Have a deep understanding of AI methodologies. Experience building large deep learning models (language, vision, events, graphs) and expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF. An engineering mindset with a track record of delivering models at scale in training data and inference. Experience delivering libraries, platform-level code, or solution-level code to existing products. A history of high-quality ideas or impactful ML projects (e.g., publications or notable projects). Ability to own and pursue a research agenda with 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/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 pre-training of large language models; publications in ACL/NAACL/EMNLP, NeurIPS, ICML, ICLR Experience training a large language model from scratch (10B+ parameters) Optimization (Training & Inference): PhD topics on optimizing training of very large models; experience with Model Sparsification, Quantization, Parallelism, Gradient Checkpointing, Model Compression; experience optimizing training for a 10B+ model Finetuning: PhD topics on guiding LLMs with further tasks; knowledge of transfer learning and model guidance; experience deploying a fine-tuned LLM Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Salaries are for candidates hired to perform work within one of these locations and refer to the amount Capital One is willing to pay at the time of posting. Salaries for part-time roles will be prorated. Cambridge, MA: $214,500 - $244,800; McLean, VA: $214,500 - $244,800; New York, NY: $234,000 - $267,000; San Francisco, CA: $234,000 - $267,000; San Jose, CA: $234,000 - $267,000. Other locations follow respective pay ranges. This role is eligible for performance-based incentives. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits. Eligibility varies by status. This role is expected to accept applications for a minimum of 5 business days. No agencies, EOE, including disability/vet. Capital One complies with applicable laws on criminal background inquiries. For accommodations, please contact RecruitingAccommodation@capitalone.com. For technical support or questions about Capital One's recruiting process, please email Careers@capitalone.com. Capital One is not liable for third-party products or services and may post roles for Capital One Canada, Europe, or COPSSC as applicable. Seniority level: Mid-Senior level. Employment type: Full-time. Job function: Research, Analyst, and Information Technology.
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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. Translate the complexity of your work into tangible business goals. The Ideal Candidate
You love the process of analyzing and creating, and are committed to making the right decision for customers. Innovative. You continually research and evaluate emerging technologies and stay current on published state-of-the-art methods and applications. Creative. You thrive on defining big problems, asking questions, and sharing new ideas. A leader. You challenge conventional thinking and mentor others; you’re passionate about talent development. Technical. You are comfortable with open-source languages and have hands-on experience developing AI foundation models and solutions using open-source tools and cloud platforms. Have a deep understanding of AI methodologies. Experience building large deep learning models (language, vision, events, graphs) and expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF. An engineering mindset with a track record of delivering models at scale in training data and inference. Experience delivering libraries, platform-level code, or solution-level code to existing products. A history of high-quality ideas or impactful ML projects (e.g., publications or notable projects). Ability to own and pursue a research agenda with 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/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 pre-training of large language models; publications in ACL/NAACL/EMNLP, NeurIPS, ICML, ICLR Experience training a large language model from scratch (10B+ parameters) Optimization (Training & Inference): PhD topics on optimizing training of very large models; experience with Model Sparsification, Quantization, Parallelism, Gradient Checkpointing, Model Compression; experience optimizing training for a 10B+ model Finetuning: PhD topics on guiding LLMs with further tasks; knowledge of transfer learning and model guidance; experience deploying a fine-tuned LLM Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Salaries are for candidates hired to perform work within one of these locations and refer to the amount Capital One is willing to pay at the time of posting. Salaries for part-time roles will be prorated. Cambridge, MA: $214,500 - $244,800; McLean, VA: $214,500 - $244,800; New York, NY: $234,000 - $267,000; San Francisco, CA: $234,000 - $267,000; San Jose, CA: $234,000 - $267,000. Other locations follow respective pay ranges. This role is eligible for performance-based incentives. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits. Eligibility varies by status. This role is expected to accept applications for a minimum of 5 business days. No agencies, EOE, including disability/vet. Capital One complies with applicable laws on criminal background inquiries. For accommodations, please contact RecruitingAccommodation@capitalone.com. For technical support or questions about Capital One's recruiting process, please email Careers@capitalone.com. Capital One is not liable for third-party products or services and may post roles for Capital One Canada, Europe, or COPSSC as applicable. Seniority level: Mid-Senior level. Employment type: Full-time. Job function: Research, Analyst, and Information Technology.
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