Lead AI Engineer (Gen AI & LLM Infrastructure) - New York

At Capital One, we are committed to creating innovative and reliable AI systems that transform banking for the better. As an industry leader in utilizing machine learning for personalized customer experiences, we invest in cutting-edge technology and top-tier talent to enhance our capabilities. Our Intelligent Foundations and Experiences (IFX) team plays a crucial role in realizing our AI vision, collaborating with partners across the organization to advance AI engineering. In this role, youll have the opportunity to impact millions of customers and contribute to breakthrough AI initiatives. We offer a competitive salary range based on location, along with a comprehensive benefits package that supports your overall well-being.

- Bachelors degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields, with a minimum of 4 years of experience in developing AI and ML algorithms or technologies, or a Masters degree in similar fields along with at least 2 years of experience.
- At least 4 years of programming experience with Python, Go, Scala, or Java.
- Proven background in deploying scalable and responsible AI solutions on cloud platforms (e.g., AWS, Google Cloud, Azure).
- Experience in designing, developing, and supporting AI services.
- Familiarity with the development of AI and ML algorithms or technologies like LLM Inference, Similarity Search, and VectorDBs using Python, C++, C#, Java, or Golang.
- Knowledge of techniques for optimizing training and inference software to enhance hardware utilization, latency, throughput, and cost.
- Strong interest in staying updated with the latest AI research and the application of new techniques in production.

- Collaborate with a diverse team including engineers, research scientists, technical program managers, and product managers to deliver AI-driven products that enhance our processes and customer interactions.
- Design, create, test, deploy, and maintain AI software components such as foundation model training, large language model inference, similarity search, guardrails, and model governance.
- Utilize a wide array of Open Source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
- Innovate and implement cutting-edge LLM optimization techniques to enhance the performance of large-scale production AI systems, focusing on scalability, cost, latency, and throughput.
- Contribute to the strategic vision and long-term planning of foundational AI systems at Capital One.