AI Engineer 4 (Vision model (VLM) customization experience)

The AI Engineer 4 role at Capital One focuses on customizing and deploying AI systems for production use, with specific experience in vision model (VLM) customization and foundation model workflows. This position emphasizes end-to-end architecture ownership, reliability practices, and optimization of training and inference at scale.

Location

New York, NY (onsite)

Compensation

USD 215,200 - 245,600 per year

Team

The Intelligent Foundations and Experiences (IFX) team is central to bringing Capital One’s AI vision to life. The team partners across the company to advance science and AI engineering, building and deploying proprietary solutions that support business value and deliver impact for customers.

IFX AI models and platforms enable teams across Capital One to enhance products with responsible and scalable AI.

Responsibilities

• Collaborate with cross-functional partners including engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for associates and customers.
• 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.
• Apply a broad stack of Open Source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and additional tools.
• Develop and introduce foundation model optimization techniques that improve production performance, including scalability, cost, latency, and throughput.
• Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
• Own end-to-end architecture for complex AI systems, with a focus on maintainability, observability, and ethical alignment.
• Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift.
• Work with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
• Lead cross-functional technical reviews for new AI deployments, ensuring security, data governance, and compliance standards are met.
• Mentor Principal and Senior Associates on scalable design, performance tuning, and translating research into production.

Requirements

• Education and experience: Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies; or Master’s degree in a related field plus at least 2 years of experience developing AI and ML algorithms or technologies.
• Programming: At least 4 years programming with Python, Go, Scala, CUDA, or Java.
• Experience leading development of AI systems involving tradeoffs among cost, latency, throughput, and accuracy.
• Cloud deployment: 6 years deploying scalable and responsible AI solutions on cloud platforms (e.g., AWS, Google Cloud, Azure, or equivalent private cloud).
• Experience designing, developing, delivering, and supporting AI services.
• Experience developing AI and ML algorithms or technologies (e.g., LLM inference, similarity search and vector databases, guardrails, memory) using Python, C++, C#, Java, CUDA, or Golang.
• Experience applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
• Experience building agentic AI systems and agentic workflows.
• Proficiency designing distributed systems for model training, evaluation, and online inference at petabyte scale.
• Experience defining AI model governance processes, including producibility, lineage tracking, and automated retention schedules.
• Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.

Technologies

• AWS Ultraclusters
• Huggingface
• VectorDBs
• PyTorch
• AWS, Google Cloud, Azure
• Python, Go, Scala, CUDA, Java, C++, C#, Golang
• GPU, TPU
• LLM Inference, Similarity Search
• Guardrails, Memory

Benefits

• Comprehensive, competitive, and inclusive set of health, financial, and other benefits supporting total well-being.
• Performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).

Ideal Candidate

• Enjoys building systems and takes pride in work quality.
• Shares an interest in doing the right thing.
• Stays current with the latest research, with the ability to understand scientific publications and apply novel techniques in production.
• Can bring clarity to big, undefined problems and adapt quickly.
• Asks questions, investigates root causes, and communicates findings clearly.
• Shares new ideas even when they are not yet proven.
• Is deeply technical with strong foundations in engineering and mathematics, with experience across hardware, software, and AI to identify optimization opportunities.
• Can take initiative in unclear paths to achieve business goals.

Additional Information

• Expected application acceptance: minimum of 5 business days.
• No agencies please.
• Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
• Capital One promotes a drug-free workplace.
• For accommodations related to applying: contact Capital One Recruiting at 1-800-304-9102 or [email protected].
• For technical support or questions about the recruiting process: email [email protected].
• Capital One does not provide, endorse, nor guarantee third-party products, services, educational tools, or other information available through this site.