Lead AI Engineer (Vision model customization, VML)
Job Description
Lead AI Engineer focusing on vision model customization and LLM optimization within Capital One's Intelligent Foundations and Experiences (IFX) team, delivering AI powered products and scalable, high‑performance AI infrastructure, onsite in McLean, VA, with a salary range of USD 197,300 - 225,100 per year.
Responsibilities
- Collaborate with a cross‑functional team of engineers, research scientists, technical program managers, and product managers to deliver AI powered products that transform how our associates work and how our 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 introduce state‑of‑the‑art LLM optimization techniques to improve performance metrics such as scalability, cost, latency, and throughput of large scale production AI systems.
- Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
Technologies
- AWS Ultraclusters
- Huggingface
- VectorDBs
- Nemo Guardrails
- PyTorch
- Python
- Go
- Scala
- Java
- C++
- C#
- AWS
- Google Cloud
- Azure
Team Description
The Intelligent Foundations and Experiences (IFX) team sits at the core of bringing Capital One's AI vision to life. We partner across the enterprise to advance the state of the art in AI science and engineering, building and deploying proprietary solutions central to our business and delivering value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance products with the transformative power of AI.
The Ideal Candidate
You enjoy building systems, take pride in the quality of your work, and share a commitment to doing the right thing. You seek problems with the potential to change banking for good, stay current with AI research, and can judiciously apply novel techniques in production. You adapt quickly, bring clarity to complex challenges, and communicate findings concisely. You are technically deep, with a solid foundation in engineering and mathematics, and you leverage hardware, software, and AI expertise to uncover optimization opportunities others may miss. You are a resilient trailblazer who can forge new paths to achieve business goals when the route is uncertain.
Basic Qualifications
- Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in the same fields with 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.
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 abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production.