Capital One National Association
Overview
Applied Researcher 1 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.
Responsibilities
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, Hugging Face, 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 complex work into tangible business goals through strong interpersonal communication.
The Ideal Candidate
You love the process of analyzing and creating, and focus on making the right decision for customers.
Innovative. You continually research and evaluate emerging technologies and seek opportunities to apply them.
Creative. You thrive on solving big, undefined problems and sharing new ideas.
A leader. You challenge conventional thinking and mentor others while improving processes.
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.
Has a deep understanding of AI methodologies foundations.
Experience building large deep learning models with expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF.
An engineering mindset with a track record of delivering models at scale in terms of training data and inference.
Experience delivering libraries, platform-level code, or solution-level code to existing products.
A professional with a track record of high-quality ideas or improvements in machine learning, demonstrated by publications or notable projects.
Ability to own and pursue a research agenda, including choosing impactful problems and 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 start date, or an MS in 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 industrial NLP research experience.
Multiple publications on topics related to pre-training of large language models and related areas.
Experience training a large language model from scratch (10B+ parameters).
Publications in deep learning theory and venues such as ACL, NAACL, EMNLP, NeurIPS, ICML or ICLR.
Optimization: training and inference for very large models, including techniques such as model sparsification, quantization, parallelism, gradient checkpointing, and model compression.
Experience with compiler design and deploying fine-tuned LLMs.
Demonstrated ability to own research direction with high-quality ideas and results.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Compensation and Benefits The minimum and maximum full-time annual salaries for this role are listed below by location. Salaries for part-time roles will be prorated. Location-specific ranges are:
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
Candidates hired in other locations will follow the pay range for that location. This role may be eligible for performance-based incentives, including cash bonuses and long-term incentives.
Capital One offers comprehensive health, financial and other benefits. Learn more on the Capital One Careers website. Eligibility varies by status.
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).
If you require accommodations during the application process, contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information provided will be kept confidential for accommodation purposes.
Careers-related questions can be sent to Careers@capitalone.com.
Capital One does not guarantee third-party products or services available through external sites. Capital One Financial is made up of several entities; positions posted in Canada are for Capital One Canada, in the UK for Capital One Europe, and in the Philippines for COPSSC.
#J-18808-Ljbffr
Applied Researcher 1 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.
Responsibilities
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, Hugging Face, 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 complex work into tangible business goals through strong interpersonal communication.
The Ideal Candidate
You love the process of analyzing and creating, and focus on making the right decision for customers.
Innovative. You continually research and evaluate emerging technologies and seek opportunities to apply them.
Creative. You thrive on solving big, undefined problems and sharing new ideas.
A leader. You challenge conventional thinking and mentor others while improving processes.
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.
Has a deep understanding of AI methodologies foundations.
Experience building large deep learning models with expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF.
An engineering mindset with a track record of delivering models at scale in terms of training data and inference.
Experience delivering libraries, platform-level code, or solution-level code to existing products.
A professional with a track record of high-quality ideas or improvements in machine learning, demonstrated by publications or notable projects.
Ability to own and pursue a research agenda, including choosing impactful problems and 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 start date, or an MS in 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 industrial NLP research experience.
Multiple publications on topics related to pre-training of large language models and related areas.
Experience training a large language model from scratch (10B+ parameters).
Publications in deep learning theory and venues such as ACL, NAACL, EMNLP, NeurIPS, ICML or ICLR.
Optimization: training and inference for very large models, including techniques such as model sparsification, quantization, parallelism, gradient checkpointing, and model compression.
Experience with compiler design and deploying fine-tuned LLMs.
Demonstrated ability to own research direction with high-quality ideas and results.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Compensation and Benefits The minimum and maximum full-time annual salaries for this role are listed below by location. Salaries for part-time roles will be prorated. Location-specific ranges are:
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
Candidates hired in other locations will follow the pay range for that location. This role may be eligible for performance-based incentives, including cash bonuses and long-term incentives.
Capital One offers comprehensive health, financial and other benefits. Learn more on the Capital One Careers website. Eligibility varies by status.
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).
If you require accommodations during the application process, contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information provided will be kept confidential for accommodation purposes.
Careers-related questions can be sent to Careers@capitalone.com.
Capital One does not guarantee third-party products or services available through external sites. Capital One Financial is made up of several entities; positions posted in Canada are for Capital One Canada, in the UK for Capital One Europe, and in the Philippines for COPSSC.
#J-18808-Ljbffr