PhD AI Engineering Intern

What you'll do

• Prototype and ship AI-native products that reach millions of customers.
• Research, prototype, and productionalize high-impact AI systems like multimodal search and autonomous agentic workflows.
• Design and optimize AI stack infrastructure including fine-tuning pipelines, reinforcement learning, and inference optimization.
• Implement robust guardrails and sophisticated evaluation frameworks for AI systems.
• Architect agentic workflows that enable AI systems to autonomously navigate tools and orchestrate multi-step reasoning.
• Integrate AI workflows with complex microservice environments using AWS Ultraclusters and PyTorch.
• Translate research papers into production-ready code and scalable AI infrastructure.

What we're looking for

• Must be currently pursuing a PhD in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field by August 2029.
• Must be continuing in the same course of study of the most recent degree following the internship period.
• Must have at least 1 year of experience or academic work developing AI and ML algorithms or technologies.
• Must have at least 1 year of experience or academic work programming with Python, Go, Scala, or Java.
• Must be located in the continental United States for in-person attendance.
• Experience or academic work with deploying AI/ML systems on cloud platforms (preferred).
• Experience or academic work in developing and applying state-of-the-art techniques for optimizing AI/ML training or inference pipelines (preferred).
• Experience or academic work with AI/ML domains such as LLM Inference, Search and Retrieval, NLP, or Computer Vision (preferred).