Lead AI Engineer (Vision model customization, VML)

Lead AI Engineer focusing on vision model customization and LLM optimization within Capital One's Intelligent Foundations and Experiences (IFX) team.

Responsibilities

• Collaborate with engineers, research scientists, technical program managers, and product managers to deliver AI powered products that transform how associates work and how customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components including 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 such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
• Invent and apply state-of-the-art LLM optimization techniques to improve scalability, cost, latency, and throughput of large scale production AI systems.
• Contribute to the technical vision and long term roadmap of foundational AI systems at Capital One.

Requirements

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of AI/ML algorithm or technology development experience, or a Master's degree in the same fields plus at least 2 years of experience.
• At least 4 years of experience programming with Python, Go, Scala, or Java.
• 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 abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production.

Technologies

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

Team overview

The Intelligent Foundations and Experiences (IFX) team centers Capital One's AI initiatives, partnering across the company to advance AI engineering and deploy proprietary solutions that deliver value to millions of customers. Our AI models and platforms empower teams to elevate products with AI at scale.

The ideal candidate

• Enjoys building systems, takes pride in high quality work, and aligns with responsible engineering practices to improve banking.
• Keeps up with the latest AI research and can digest publications to apply techniques in production.
• Adapts quickly toDefine ambiguous problems, asks focused questions, communicates findings clearly, and proposes new ideas when appropriate.
• Is deeply technical, with a strong foundation in engineering and mathematics; leverages hardware, software, and AI optimization opportunities.
• Acts as a resilient trail blazer who can forge new paths to meet business goals when the route is unclear.

Basic qualifications

• Bachelor's degree with 4+ years of AI/ML development experience or a Master's degree with 2+ years of AI/ML development experience.
• At least 4 years of experience programming with Python, Go, Scala, or Java.

Preferred qualifications

• 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (AWS, Google Cloud, Azure, or equivalent private cloud).
• Experience designing, developing, delivering, and supporting AI services.
• Experience developing AI/ML algorithms or technologies (LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang.
• Experience 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.