Capital One seeks a Lead AI Engineer to advance responsible AI systems and scale AI powered products. The role focuses on FM Hosting and LLM Inference, partnering with the IFX team to push foundation model training, LLM inference, guardrails, and observability. This onsite position is based in McLean, VA, with a salary ranging from USD 197,300 to 225,100 per year.
Responsibilities
- Partner with a cross functional team of 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 others.
- Invent and apply state of the art LLM optimization techniques to improve performance metrics for large scale production AI systems, including scalability, cost, latency, and throughput.
- Contribute to the technical vision and the 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 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 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
- AWS Ultraclusters
- Huggingface
- VectorDBs
- Nemo Guardrails
- PyTorch
- Python
- Go
- Scala
- Java
Benefits
- Health benefits
- Financial benefits
- Performance based incentive compensation (cash bonuses and/or long term incentives)
Team Description
The Intelligent Foundations and Experiences (IFX) team is at the center of bringing Capital One's AI vision to life. We collaborate with partners across the company to advance the state of the art in AI science and engineering, and we build and deploy proprietary solutions central to the business, delivering value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI.
The Ideal Candidate
You love to build systems, take pride in code quality, and share a commitment to doing the right thing. You seek problems that can drive meaningful change in banking. You stay current with the latest AI research and can interpret publications to judiciously apply new techniques in production.
You adapt quickly and bring clarity to large, undefined problems. You ask questions, dig into root causes, and articulate findings concisely. You are comfortable proposing ideas even if they are unproven.
You are deeply technical with a strong foundation in engineering and mathematics, and your expertise across hardware, software, and AI helps you identify optimization opportunities others miss.
You are a resilient trailblazer who can create new paths to achieve business goals when the route is unclear.
Basic 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 in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields 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
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 apply novel techniques in production
