AI Engineering Intern

Jobtailor; California (MO); On-site; USD 34,440,000 - 44,083,000; Part time

Job summary

Capital One is seeking a PhD candidate to intern on AI-native product development, prototyping, and productionalization of AI systems. You will collaborate with research scientists, product managers, and engineers to ship advanced AI capabilities across multimodal search and intelligent document processing.

The role emphasizes Python/Java programming, AWS deployment, and experimentation with LLMs, reinforcement learning, and NLP. In-person at the assigned U.S. location; continental US only.

Qualifications

• PhD in Computer Science, AI, Electrical Engineering, Computer Engineering or related field, with degree expected by Aug 2029 or earlier

Responsibilities

• Partner with research scientists, product managers, and engineers to prototype and ship AI-native products
• Research, prototype, and productionalize AI systems including multimodal search, intelligent document processing, and autonomous agentic workflows
• Design and optimize AI infrastructure including fine-tuning/pre-training pipelines, reinforcement learning, inference optimization, guardrails, and evaluation frameworks
• Build AI systems using AWS Ultraclusters, PyTorch, and agentic frameworks
• Architect agentic workflows that navigate tools, orchestrate multi-step reasoning, and integrate with complex microservice environments
• Build Agentic AI applications and platform capabilities for customer-facing GenAI workflows, AI infrastructure, and internal agentic coding tools
• Contribute to AI systems and AI-native experiences serving Capital One’s 100mm+ customers

Skills

Python programming

Java programming

Cloud deployment

PyTorch

LangChain familiarity

Agentic frameworks familiarity

Education

PhD in Computer Science/AI

Tools

AWS Ultraclusters

LangChain

LangGraph

LlamaIndex

Autogen

MCP/A2A

Frontier-Labs Agent SDKs

Job description

• Partner with research scientists, product managers, and engineers to prototype and ship AI-native products
• Research, prototype, and productionalize high-impact AI systems, including multimodal search, intelligent document processing, and autonomous agentic workflows
• Design and optimize AI infrastructure, including fine-tuning and pre-training pipelines, reinforcement learning, inference optimization, guardrails, and evaluation frameworks
• Use AWS Ultraclusters, PyTorch, and agentic frameworks to build AI systems
• Architect agentic workflows that navigate tools, orchestrate multi-step reasoning, and integrate with complex microservice environments
• Build Agentic AI applications and platform capabilities for customer-facing GenAI workflows, AI infrastructure, and internal agentic coding tools
• Contribute to AI systems and AI-native experiences serving Capital One’s 100mm+ customers

Requirements

• Currently has, or is in the process of obtaining, a PhD in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, with the degree expected by August 2029 or earlier
• Must continue in the same course of study of the most recent degree after the internship
• At least 1 year of experience or academic work developing AI and ML algorithms or technologies
• At least 1 year of experience or academic work programming with Python, Go, Scala, or Java
• Must be located in the continental United States
• In-person attendance at the assigned location required for the internship duration
• Experience or academic work deploying AI/ML systems on cloud platforms such as AWS, Google Cloud, or Azure
• Experience or academic work developing and applying state-of-the-art techniques for optimizing AI/ML training or inference pipelines, including distributed GPU computational frameworks
• Experience or academic work with AI/ML domains and systems such as LLM inference, search and retrieval, NLP, computer vision, guardrails, or memory
• Familiarity with agentic frameworks such as LangChain, LangGraph, LlamaIndex, Autogen, MCP/A2A, or frontier-labs agent SDKs

Core Competencies

Demonstrates expertise in developing and optimizing AI systems, including multimodal search and intelligent document processing, while leveraging cloud platforms like AWS. Proficient in programming languages such as Python and Java, with a strong foundation in AI/ML algorithms and frameworks.

Highest-signal resume keywords

• PhD In Computer Science, AI, Electrical Engineering, Or Related Field
• AI/ML Algorithm Development
• Python Programming
• AWS Deployment
• Agentic Frameworks Familiarity

Hard Skills

• AI System Prototyping
• Machine Learning Algorithms
• Reinforcement Learning
• Inference Optimization
• Multimodal Search
• NLP
• Computer Vision
• Distributed GPU Frameworks
• Fine-Tuning Pipelines
• Pre-Training Pipelines

Industry Keywords

• AI-Native Products
• Agentic Workflows
• Cloud Platforms
• AI Infrastructure
• Customer-Facing GenAI Workflows

Tools & Technologies

• AWS Ultraclusters
• PyTorch
• LangChain
• LangGraph
• LlamaIndex
• Autogen
• MCP/A2A
• Frontier-Labs Agent SDKs