At Capital One, we are creating responsible and reliable AI systems, changing banking for good. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI.
In this role, you will:
Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change 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 the performance — scalability, cost, latency, throughput — of large scale production AI systems.
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
Qualifications
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in the same fields plus at least 8 years of experience.
At least 10 years of experience programming with Python, Go, Scala, or Java.
Requirements
9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud).
Experience architecting, designing, developing, integrating, delivering, and supporting complex enterprise AI systems.
Demonstrated ability to lead and mentor an engineering organization and influence cross-functional stakeholders up to the SVP level.
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.
Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers.
Experience building and deploying multi-modal models for technologies like computer vision, speech recognition, optical character recognition, or other sensor systems in applications such as robotics, digital assistants, industrial automation, autonomous driving, or related.
Benefits
Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
Performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).