AI/ML Intern - Agentic Retrieval & Enterprise RAG at Zoom · Seattle

Summary: Zoom is building the next generation of enterprise AI systems that power intelligent search, retrieval, and agentic workflows across Zoom products. As an AI Engineer / Machine Learning Engineer Intern, you will work on agentic retrieval and Enterprise RAG systems that operate at production scale and directly impact real users. Responsibilities: - Design and implement agentic retrieval pipelines that orchestrate multi-step reasoning, retrieval, and tool or function calls - Improve end-to-end performance of Enterprise RAG systems, including latency, throughput, and cost efficiency - Integrate agentic workflows with unified retrieval layers and enterprise data sources - Optimize retrieval strategies to reduce redundant calls and unnecessary context expansion - Implement content compression or filtering techniques to improve reasoning efficiency while preserving answer quality - Analyze retrieval and function-call traces to identify inefficiencies and failure patterns - Build scalable, maintainable ML and retrieval components suitable for production environments - Add instrumentation, logging, and evaluation hooks to measure system behavior and product impact - Collaborate with engineers and researchers to transition prototypes into reliable services Required Qualifications: - Be currently pursuing a BS, MS, or PhD in Computer Science, Machine Learning, or a related field - Have programming skills in Python and familiarity with production ML or backend systems - Have a solid understanding of information retrieval, NLP, or machine learning fundamentals - Have experience or coursework related to LLMs, retrieval-augmented generation, or agent-based systems - Have the ability to reason about system trade-offs such as accuracy, latency, and cost Preferred Qualifications: - Have hands-on experience with LLM APIs, prompt engineering, or fine-tuning - Have familiarity with search systems, vector databases, or ranking pipelines - Have exposure to agentic workflows, tool or function calling, or multi-step reasoning systems - Have experience working with real datasets and evaluating model or system performance - Have an interest in building AI systems with direct product impact, not just research prototypes Required Skills: Python, Machine Learning, Information Retrieval Important Skills: NLP, LLMs, Production Engineering Nice-to-Have Skills: Curiosity, Collaboration, Clear Communication Benefits: Hands-on experience building production-facing AI systems used at enterprise scale, Exposure to state-of-the-art agentic retrieval and Enterprise RAG architectures, Mentorship from experienced AI engineers and ML practitioners, Opportunity to see your work influence real Zoom products and user experiences, A strong foundation for a career in applied AI, ML engineering, or AI platform development