Senior AI Engineer, Foundation Models & LLMs

Capital One; California; Hybrid; USD 251,000 - 286,000; Full time

Job summary

Capital One is seeking an AI Engineer 5 (MLXT) to advance responsible AI across the enterprise. You will design, build, test, and deploy AI software components including foundation models, multi-model pipelines, and inference at scale.

You will collaborate with cross-functional teams, optimize performance and cost, and help govern AI systems while mentoring engineers as Capital One scales its AI platforms.

Qualifications

• 6+ years of experience developing AI and ML algorithms or technologies.
• 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (AWS, GCP, Azure).
• Experience designing, developing, delivering, and supporting complex AI systems with LLMs, vector search and guardrails.

Responsibilities

• Partner with a cross-functional team of engineers, researchers, and product managers to deliver AI-powered products.
• 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.
• Invent and introduce state-of-the-art foundation model optimization techniques to improve performance, scalability, cost, latency, throughput.
• Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One.

Skills

Python

LLM Inference

VectorDBs

PyTorch

HuggingFace

GPU/CUDA

Cloud platforms

Education

Bachelor's degree in Computer Science, AI, Electrical Engineering, or related fields

Master's degree in Computer Science, AI, Electrical Engineering, or related fields

Tools

AWS

GCP

Azure

VectorDBs

PyTorch

HuggingFace

CUDA

Job description

Capital One is seeking an AI Engineer 5 (MLXT) to advance responsible AI across the enterprise. You will design, build, test, and deploy AI software components including foundation models, multi-model pipelines, and inference at scale.

You will collaborate with cross-functional teams, optimize performance and cost, and help govern AI systems while mentoring engineers as Capital One scales its AI platforms.