Leadership role focused on the design, development, and deployment of AI-powered products, foundation model training, and scalable-performance AI infrastructure.
Locations (6)
United States
Cambridge, Massachusetts, United States
McLean, Virginia, United States
New York, New York, United States
San Francisco, California, United States
San Jose, California, United States
Compensation
Remote (Regardless of Location): $286,200 - $326,700 for Sr. Director, AI Engineer; Cambridge, MA: $314,800 - $359,300 for Sr. Director, AI Engineer; McLean, VA: $314,800 - $359,300 for Sr. Director, AI Engineer; New York, NY: $343,400 - $392,000 for Sr. Director, AI Engineer; San Francisco, CA: $343,400 - $392,000 for Sr. Director, AI Engineer; San Jose, CA: $343,400 - $392,000 for Sr. Director, AI Engineer
Responsibilities
Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products.
Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
Contribute to the technical vision and the long term roadmap of foundational AI systems.
Requirements
Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
Nice to have: 7+ years of experience managing and leading an engineering team
Nice to have: 8+ years of experience deploying scalable and responsible AI solutions on cloud platforms
The AI Foundations team focuses on bringing the vision for AI at Capital One to life, covering the entire research life cycle from academic partnerships to building production systems.
Locations (4)
New York, New York, United States
Cambridge, Massachusetts, United States
McLean, Virginia, United States
San Jose, California, United States
Compensation
Cambridge, MA: $218,700 - $249,600; McLean, VA: $218,700 - $249,600; New York, NY: $238,700 - $272,300; San Jose, CA: $238,700 - $272,300
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.
The AI Engineer 5 will design, develop, test, and support AI software components including foundation model training, LLM inference, agents, and multi-agent workflows to reimagine banking services for customers.
Compensation
The minimum and maximum full-time annual salaries for this role are listed below, by location... actual salary offered to any candidate at the time of hire will be reflected in candidate’s offer letter.
Responsibilities
Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products.
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
Invent and introduce state-of-the-art foundation model optimization techniques to improve performance — scalability, cost, latency, throughput.
Contribute to the technical vision and the long term roadmap of foundational AI systems.
Requirements
Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
The AI Foundations team focuses on bringing the vision for AI to life across the entire research life cycle, from academia to building production systems.
Locations (5)
Cambridge, Massachusetts, United States
McLean, Virginia, United States
New York, New York, United States
San Francisco, California, United States
San Jose, California, United States
Compensation
The minimum and maximum full-time annual salaries for this role are listed below, by location. Cambridge, MA: $262,500 - $299,600; McLean, VA: $262,500 - $299,600; New York, NY: $286,400 - $326,800; San Francisco, CA: $286,400 - $326,800; San Jose, CA: $286,400 - $326,800
The AI Foundations team is at the center of bringing our vision for AI at Capital One to life, partnering with cross-functional teams to deliver AI-powered products.
Locations (5)
Cambridge, Massachusetts, United States
McLean, Virginia, United States
New York, New York, United States
San Francisco, California, United States
San Jose, California, United States
Compensation
The minimum and maximum full-time annual salaries for this role are listed below, by location. Cambridge, MA: $218,700 - $249,600; McLean, VA: $218,700 - $249,600; New York, NY: $238,600 - $272,300; San Francisco, CA: $238,600 - $272,300; San Jose, CA: $238,600 - $272,300
The AI Engineer will design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, and multi-agent workflows to reimagine how Capital One serves its customers.
Locations (3)
McLean, Virginia, United States
New York, New York, United States
San Jose, California, United States
Compensation
McLean, VA: $197,300 - $225,100 for AI Engineer 4; New York, NY: $215,200 - $245,600 for AI Engineer 4; San Jose, CA: $215,200 - $245,600 for AI Engineer 4
Responsibilities
Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products.
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Responsibilities
Partner with cross-functional teams of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products
Leverage technologies such as Pytorch, AWS Ultraclusters, Huggingface, Lightning to analyze large datasets
Build AI foundation models through design, training, evaluation, validation and implementation
Engage in high impact applied research to advance AI capabilities
Define and steward novel research directions
Requirements
PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields
M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields
Nice to have: PhD focus on NLP
Nice to have: Masters with 10 years of industrial NLP research experience
Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, 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.
Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products.
Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents and multi-agent workflows.
Invent and introduce state-of-the-art foundation model optimization techniques.
Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment.
Define and maintain service-level objectives (SLOs) for AI reliability.
Partner with a cross-functional team of data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products.
Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal insights 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.
Lead cross-functional research threads that bridge prototype model development and deployment with ML engineering partners.
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, 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.