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

This role focuses on customizing and deploying AI systems for production at scale, including foundation model work and vision model (VLM) customization experience. You will help shape architecture, reliability, and evaluation practices while optimizing training and inference for performance, cost, and throughput.

Location

New York, NY (onsite)

Compensation

USD 215,200 - 245,600 per year

Experience Level

Minimum 4 years of relevant experience.

Team

The Intelligent Foundations and Experiences (IFX) team is central to delivering Capital One’s vision for AI. The team partners across the company to advance science and AI engineering, builds and deploys proprietary solutions, and supports teams in adding AI capabilities in responsible and scalable ways.

Key Responsibilities

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that support how associates work and how customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components across foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• Apply a broad set of Open Source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and others.
• Develop and introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput for production AI systems.
• Contribute to technical direction and the long-term roadmap for foundational AI systems at Capital One.
• Own end-to-end architecture for complex AI systems, with focus on maintainability, observability, and ethical alignment.
• Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift.
• Collaborate with infrastructure engineering to optimize GPU/TPU utilization and improve model inference pipeline performance.
• Lead cross-functional technical reviews for new AI deployments, including security, data governance, and compliance standards.
• Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation.

Required Qualifications

• 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 a Master’s Degree plus at least 2 years of experience.
• At least 4 years of programming experience with Python, Go, Scala, CUDA, or Java.
• Experience leading AI system development with tradeoffs across cost, latency, throughput, and accuracy.
• 6 years of experience deploying scalable and responsible AI solutions on cloud platforms such as 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 VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang.
• Experience building and applying state-of-the-art optimization techniques for 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).

Additional Information

• 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) committed to non-discrimination in compliance with applicable federal, state, and local laws.
• Capital One promotes a drug-free workplace.
• If you need an accommodation to apply, contact Capital One Recruiting at 1-800-304-9102 or [email protected].
• For technical support or questions about Capital One’s recruiting process, email [email protected].
• Capital One does not provide, endorse, or guarantee third-party products, services, educational tools, or other information available through this site.