Lead AI Engineer (Vision model customization, VLM)

At Capital One, this Lead AI Engineer role focuses on building responsible and reliable AI systems in a setting where teams work across engineering, research, and product. You will help design and deliver AI-powered experiences, with a particular emphasis on vision model customization and VLM, from foundation model training through production evaluation and guardrails.

This is an onsite position in McLean, VA 22101. The salary range is USD 197,300 - 225,100 per year, and the role includes performance based incentive compensation with potential cash bonuses and/or long term incentives (LTI). Capital One also offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits to support total well-being.

What you’ll do

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how associates work and how customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components spanning foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• Leverage a broad stack of open source and SaaS AI technologies including AWS Ultraclusters, Hugging Face, VectorDBs, NVIDIA Nemo Guardrails, and PyTorch.
• Introduce state-of-the-art LLM optimization techniques to improve production performance across scalability, cost, latency, and throughput.
• Contribute to the technical vision and the long-term roadmap for foundational AI systems at Capital One.

Basic qualifications

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, 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.
• At least 4 years of experience programming with Python, Go, Scala, or Java.

Technologies you may work with

• AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch
• Python, Go, Scala, Java, C++, C#, Golang
• AWS, Google Cloud, Azure

Preferred qualifications

• 6 years of experience 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 VectorDBs, guardrails, memory) using Python, C++, C#, Java, or Golang.
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
• Passion for staying current with AI research and AI systems, and applying novel techniques in production.