
location_onNYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States
At Capital One, we are creating responsible and reliable AI systems to change banking for good. For years, we have been an industry leader in using machine learning to create real-time, personalized customer experiences. 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 industry-leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.
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 partners across the company to advance the state of the art in science and AI engineering. 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.
As a Distinguished AI Engineer, 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. You will 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.
In this role, you will invent and introduce state-of-the-art LLM optimization techniques to improve the performance, scalability, cost, latency, and throughput of large-scale production AI systems. You will contribute to the technical vision and the long-term roadmap of foundational AI systems at Capital One. You are expected to be a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown, bringing clarity to big, undefined problems.
Capital One is committed to a fair and transparent hiring process. We consider qualified applicants regardless of background. For specific details on the interview stages and timeline, please refer to the communication from our recruiting team upon application submission.
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. We promote a drug-free workplace and consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws. We are dedicated to building a diverse and inclusive environment where everyone can do their best work.
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Work model: On-site
NYU Paulson Center, 181, Mercer Street, University Village, Manhattan, New York County, New York, 10012, United States
New York, New York
8 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 VP 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; Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production; Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers
Skills: Machine Learning, Ai, Aws, Huggingface, Vectordbs, Nemo Guardrails, Pytorch, LLM Inference, Similarity Search, Python.
Education: Bachelor's degree in CS, AI, EE, CE, or related fields with 8+ years experience; Master's degree in CS, AI, EE, CE, or related fields with 6+ years experience.