Capital One is seeking a Senior Lead AI Engineer to help design and deploy founding AI platform services. This onsite role in McLean, VA offers a competitive salary range of USD 229,900 to 262,400 per year as you lead cross functional teams delivering AI powered products that transform how associates work and how customers interact with Capital One.
Overview
At Capital One, the aim is to build responsible and reliable AI systems that drive safer, smarter banking. The company has a track record of using machine learning to create real time, personalized experiences for customers, supported by a strong technology foundation and deep expertise in AI research.
Responsibilities
- Collaborate with a cross functional team of engineers, research scientists, technical program managers, and product managers to deliver AI powered products that alter how associates work and how customers engage 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 performance metrics such as scalability, cost, latency, and throughput for 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
Basic Qualifications
- Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master'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
- At least 6 years of experience programming with Python, Go, Scala, or Java
Preferred Qualifications
- 7 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, integrating, delivering, and supporting complex AI systems
- Demonstrated ability to lead and mentor an engineering team and influence cross functional stakeholders
- 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 apply novel techniques in production
- Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers
Overview
The Intelligent Foundations and Experiences (IFX) team sits at the heart of Capital One's AI vision. The team partners across the company to advance AI research and engineering, building and deploying proprietary solutions that support the business and deliver value to millions of customers.
The Ideal Candidate
- Enjoys building robust systems and takes pride in code quality, with a commitment to doing the right thing
- Keeps up with the latest AI research and can translate publications into production ready techniques
- Adaptable and capable of bringing clarity to large, undefined problems, with precise communication of findings
- Technically deep in engineering and mathematics, with the ability to optimize across hardware, software, and AI
- A resilient trailblazer who can chart paths to meet business goals when the route is uncertain
Team Description
The IFX team collaborates closely with partners across Capital One to push the frontier of AI engineering. By building and deploying proprietary AI models and platforms, the team enables other squads to enhance products with AI and deliver value to millions of customers.
