Applied Scientist Intern at UiPath in Bellevue, WA

Summary: UiPath is a leading company in enterprise software focused on automation. They are seeking an Applied Scientist Intern to help build intelligent automation systems powered by AI, contributing to the development of AI agents that can reason and interact with various tools. Responsibilities: - Prototype and experiment with LLM-based systems, including agent workflows, tool use, retrieval-augmented generation (RAG), and multi-step reasoning - Build and evaluate coding agents and automation agents that interact with APIs, developer tools, or user interfaces - Develop Python-based prototypes, evaluation pipelines, and experimentation frameworks - Explore and apply techniques such as prompt engineering, structured outputs, memory, and planning for agent behavior - Run experiments to evaluate model and agent performance across quality, latency, and cost dimensions - Collaborate with applied scientists and engineers to integrate prototypes into product workflows - Document findings, trade-offs, and recommendations to inform team direction and product decisions Required Qualifications: - Currently pursuing an MS or PhD in Computer Science, Machine Learning, AI, or a related field - Strong programming skills in Python, with experience building projects, research prototypes, or systems - Familiarity with large language models and modern AI tooling (e.g., APIs, prompting, or agent frameworks) - Interest or experience in LLM agents, coding agents, or tool-using AI systems - Solid understanding of core machine learning concepts from coursework or research - Ability to quickly prototype ideas and iterate in a fast-paced environment - Strong problem-solving skills and curiosity about building reliable, real-world AI systems - Effective communication skills and ability to collaborate with cross-functional teams Preferred Qualifications: - Experience with agent frameworks or autonomous workflows - Exposure to RAG, fine-tuning, evaluation methods, or prompt optimization - Familiarity with software engineering best practices (version control, testing, reproducibility) - Prior internships, research experience, or open-source contributions in AI/ML Required Skills: Python, Machine Learning, Large Language Models Important Skills: AI Tooling, Prototyping