AI Engineer 4 (AI Foundations, VLM Customization)
$197k - $225k • San Jose, CA • Full-time
Posted 10d ago
About the job
Capital One is building responsible and reliable AI systems to transform banking. Leveraging deep experience in machine learning and investments in technology, the company aims to be at the forefront of enterprise AI adoption. This role is within the Intelligent Foundations and Experiences (IFX) team, which is central to realizing Capital One's AI vision. The team builds and deploys proprietary AI solutions that deliver value to millions of customers and empower other teams across the company to enhance their products with AI in responsible and scalable ways.
Responsibilities
- Partner with cross-functional teams to deliver AI-powered products.
- Design, develop, test, deploy, and support AI software components, including foundation model training, LLM inference, agents, similarity search, guardrails, model evaluation, and governance.
- Leverage Open Source and SaaS AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
- Invent and introduce state-of-the-art foundation model optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale AI systems.
- Contribute to the technical vision and roadmap for foundational AI systems.
- Own the end-to-end architecture for complex AI systems, ensuring maintainability, observability, and ethical alignment.
- Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift.
- Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
- Lead technical reviews for new AI system deployments, ensuring security, data governance, and compliance.
- Mentor associates on scalable design, performance tuning, and research-to-production translation.
Requirements
- Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, OR Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies.
- At least 4 years of programming experience with Python, Go, Scala, CUDA, or Java.
- Experience leading development of AI systems with trade-offs in cost, latency, throughput, and accuracy.
- 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g., AWS, Google Cloud, Azure, or equivalent private cloud).
- Experience designing, developing, delivering, and supporting AI services.
- 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.
- Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale.
- Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules.
- Demonstrated ability to influence architectural decisions across multiple AI projects.