Software Engineer Intern (TikTok-Generalized Arch-Code Intelligence & Quality Validation) - 2027 Summer

About the Team The Agentic Ops US team focuses on two major areas: Code Graph and Quality Validation. The code graph serves as the data foundation for validation, encompassing static relationships (function calls, experiment/instrumentation dependencies) and dynamic execution paths (reconstructed from traces). Quality validation covers static rule checking (mining soft and logical constraints) and dynamic issue detection, reproduction, and fixing. We aim to improve code reliability and R&D efficiency through systematic, data-driven approaches.

We are looking for talented individuals to join us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth. Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals. Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted. Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.

Responsibilities 1. Participate in building and optimizing the code graph, including static relationship extraction, dynamic trace data cleansing, and aggregation. 2. Develop static validation rules (logical and soft constraints) based on the graph, and contribute to the design and implementation of dynamic validation tools (issue reproduction, root cause localization). 3. Conduct in-depth analysis of production quality issues, distill general validation patterns, and drive automation coverage. 4. Research and introduce cutting-edge academic and industrial techniques in code analysis, program slicing, anomaly detection, etc., to continuously improve validation effectiveness.