AI Engineer (VLM Customization)

Salary: $197,300 - 245,600 per year Requirements: Bachelors degree in computer science, AI, electrical engineering, computer engineering, or a related field and at least 4 years of experience developing AI/ML algorithms or technologies; or a relevant masters degree and at least 2 years of that experience At least 4 years of programming experience with Python, Go, Scala, CUDA, or Java Experience customizing vision-language models (VLMs) Preferred: Experience leading AI systems development and making trade-offs among cost, latency, throughput, and accuracy Preferred: 6 years of experience deploying scalable, responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud Preferred: Experience designing, developing, delivering, and supporting AI services Preferred: Experience developing AI/ML algorithms or technologies, such as LLM inference, similarity search, vector databases, guardrails, or memory, using Python, C++, C#, Java, CUDA, or Go Preferred: Experience optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Preferred: Experience building agentic AI systems and workflows Preferred: Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Preferred: Experience defining AI model governance processes, including producibility, lineage tracking, and automated retraining schedules Preferred: Ability to influence architectural decisions across multiple AI product lines or platforms Strong engineering and mathematical foundations, with the ability to assess research and apply relevant techniques in production Adaptability in addressing ambiguous problems, investigating root causes, communicating findings clearly, and proposing new ideas Responsibilities: Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for our associates and customers Design, develop, test, deploy, and support AI software components, including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability Use open-source and SaaS AI technologies, including AWS Ultraclusters, Hugging Face, vector databases, and PyTorch Develop foundation model optimization techniques to improve the scalability, cost, latency, and throughput of large-scale production AI systems Help shape our technical vision and long-term roadmap for foundational AI systems Own end-to-end architecture for complex AI systems, with attention to maintainability, observability, and ethical alignment Define and maintain AI reliability service-level objectives, including latency, uptime, and model performance drift Work with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews of AI deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates in scalable design, performance tuning, and translating research into production Technologies: Agentic AI AI AWS Azure C# Cloud CUDA Hardware Support Java LLM Model Training PyTorch Python Scala Security Golang Machine Learning More: At Capital One, we build responsible, reliable AI systems to improve banking through personalized customer experiences and scalable AI infrastructure. Our Intelligent Foundations and Experiences team works across the company to advance AI science and engineering and develop proprietary solutions used by teams and customers. This AI Engineer 4 role is available in Cambridge, Massachusetts; McLean, Virginia; New York, New York; and San Jose, California. The listed annual salary ranges are $197,300–$225,100 in Cambridge and McLean, and $215,200–$245,600 in New York and San Jose; pay for other locations varies. The role is also eligible for performance-based incentives. We offer health, financial, and other benefits, with eligibility dependent on employment status and management level. We will consider sponsoring a qualified applicant for employment authorization. last updated 39 week of 2026