Lead applied research in AI foundations, building and deploying large-scale AI models to enhance customer experiences at Capital One.
Locations (4)
Cambridge, Massachusetts, United States
McLean, Virginia, United States
New York, New York, United States
San Jose, California, United States
Compensation
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $262,500 - $299,600 for Applied Researcher 5 McLean, VA: $262,500 - $299,600 for Applied Researcher 5 New York, NY: $286,400 - $326,800 for Applied Researcher 5 San Jose, CA: $286,400 - $326,800 for Applied Researcher 5
Responsibilities
Partner with cross-functional teams to deliver AI-powered products
Leverage technologies such as Pytorch, AWS, Huggingface, Lightning
Build AI foundation models through design, training, evaluation, validation, and implementation
Engage in high-impact applied research to advance AI capabilities
Translate research insights into tangible business goals
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 geometric deep learning
Nice to have: multiple papers at KDD, ICML, NeurIPS, ICLR
Nice to have: experience scaling graph models to >50m nodes
Experienced RAI Engineer building state of the art models to solve business challenges while focusing on responsible aspects such as AI model fairness, transparency, explainability, robustness, soundess, and privacy.
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.
Lead Systems Engineer to support government sponsors in architecting, analyzing, and advancing complex mission and enterprise systems across evolving national security environments.
Compensation
$146,400 - $183,000 - $219,600 Annual
Responsibilities
Lead the application of Model-Based System Architecting (MBSA), Model-Based Systems Engineering (MBSE), Architecture Analysis, and Digital Engineering methods to develop, evaluate, and evolve system architectures that enable informed engineering, acquisition, and investment decisions.
Apply systems engineering, model-based system architecting, and architecture analysis principles across the system lifecycle, including mission analysis, concept development, architecture definition, requirements development, integration planning, verification, validation, deployment planning, and technical transition.
Lead the development and evolution of operational, functional, logical, physical, and enterprise architectures that capture stakeholder needs, mission objectives, system behaviors, interfaces, dependencies, and implementation considerations for complex systems and systems-of-systems.
Apply MBSE, MBSA, and Digital Engineering methods to develop and maintain authoritative digital engineering artifacts that establish traceability across stakeholder needs, operational concepts, system architectures, requirements, interfaces, constraints, analyses, and verification activities within an integrated digital thread.
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
Partner with cross‑functional teams to deliver AI‑powered products that transform customer interactions and build AI foundation models.
Locations (4)
Cambridge, Massachusetts, United States
McLean, Virginia, United States
New York, New York, 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 Jose, CA: $286,400 - $326,800
Responsibilities
Partner with data scientists, software engineers, ML engineers and product managers to deliver AI‑powered products
Lead the independent validation of fraud and AI models across OKX products, establishing and maintaining a robust model risk framework.
Locations (2)
New York, New York, United States
San Jose, California, United States
Compensation
The salary range for this position is $200,000 - $300,000
Responsibilities
Establish and own the independent validation framework for fraud models and AI-enabled decision systems
Assess model conceptual soundness, intended use, assumptions, and limitations
Personally execute end-to-end model validations, including data analysis and code review
Assess AI/ML and generative AI applications for robustness, reliability, explainability, and human oversight
Perform ongoing monitoring and periodic revalidation of models
Requirements
Master’s or Ph.D. in a quantitative field such as Statistics, Mathematics, Computer Science, or equivalent
Illinois, United States
Show all 15 locations
Maine, United States
Maryland, United States
Massachusetts, United States
Minnesota, United States
New York, United States
New Jersey, United States
Ohio, United States
Virginia, United States
Washington, United States
Compensation
Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below.
Responsibilities
Developing and implementing AI models and solutions, focusing on ethical and responsible practices.
Detecting, evaluating and applying relevant RAI dimensions (bias, fairness, robustness explainability etc.) in AI systems; work on mitigating the identified risks.
Supporting client sales conversations and proposal preparation
Optimizing and maintaining existing AI systems for enhanced performance and adherence to ethical standards.
Participating in the full AI development lifecycle, including data preparation, design, coding, testing, deployment, and support.
Requirements
Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or related technical fields
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.
Conduct architecture analyses, trade studies, mission engineering assessments, and capability gap analyses to evaluate alternative architectures, emerging technologies, operational concepts, and system designs using both qualitative and quantitative techniques.
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.
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