Research Scientist Intern (Compute Platform - Database Acceleration) - 2026 Start (PhD)

Team Introduction: The Data Platform team works on challenges in big data infrastructure and data products. Our team focuses on internal tools relating to OLAP DBMS, logging and data ingestion infrastructure, A/B testing for all product and feature launches, workflow management, distributed cache, data visualization tools, and big data engineering, which supports TikTok's business products.

Data-Data Platform-Compute Platform - DB Boost team focuses on building the next generation DBMS kernel aiming for the best-in-class query latency and hardware utilization. The team operates the distributed OLAP infrastructure powering cloud native data warehouse, which is the foundation behind data-driven decision-making within TikTok.

We are looking for talented individuals to join us for an internship in 2026. PhD Internships at our Company aim to provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. PhD internships at Our Company provides students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and development events, and collaboration with industry experts. Applications will be reviewed on a rolling basis - we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date).

Online Assessment Candidates who pass resume evaluation will be invited to participate in TikTok's technical online assessment in HackerRank.

Responsibilities

• Design and develop kernel modules or core features for cloud-native distributed analytical database systems - Conduct research for cutting-edge technology evolvement in database and data management area and identify the potential future directions - Solve unique and complex problems on large-scale, high-performance cloud infrastructure - Partner with different teams on building backend support for cloud native database service