Senior Staff AI Engineer (Remote Eligible)

Capital One•San Jose, CA

1d•$286,200 - $392,000•Remote

About The Position

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. 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. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver 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, in responsible and scalable ways for the highest leverage impact.

Requirements

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 Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies
At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java

Nice To Haves

Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy
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 AI systems
Demonstrated ability to lead and mentor multiple engineering teams 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, CUDA, 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
Experience in building agentic AI systems and agentic workflows
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
Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership
Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance
Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams
Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact
Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)

Responsibilities

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, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
Invent and introduce state-of-the-art foundation model 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.
Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale
Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide
Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture
Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One’s AI technical leadership.