AI Infrastructure Engineer Intern (Compute Efficiency & Scheduling) - 2027 Start (PhD)

We decide how ByteDance's massive fleet of computers gets used — turning hundreds of clusters and millions of daily workloads (microservices, big data, and large AI/LLM jobs) into a system that's highly efficient, reliable, and increasingly self-managing, powered by our own intelligent scheduling platform Godel (open-sourced to the community). Our mission: get the most value out of every unit of computing power, at a scale few places in the world can offer, and let AI increasingly help run the infrastructure.

We are looking for talented individuals to join us for an internship.

PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.

Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.

Applications will be reviewed on a rolling basis, so we encourage you to apply early.

Please clearly state your availability in your resume (Start date, End date).

What You Might Work On One focused, real project within our scope — for example: - Help make our intelligent, AI-driven scheduler smarter at placing and balancing workloads. - Explore new ways to get more useful work out of the same hardware — smarter use of compute, memory, or power. - Build tools that help a global platform run reliably and increasingly manage itself, including AI-agent-assisted automation.

Why This Role Matters The AI era runs on compute — and using it efficiently is one of the defining challenges for our company and the whole industry.

Our team owns that challenge at ByteDance's global scale, making the infrastructure behind TikTok and our AI/LLM products faster, smarter, and far more efficient.

As an intern, you'll get a real project at the center of it.

Minimum Qualifications - Currently pursuing a PhD in Computer Science or a related discipline. - Able to commit to a 12-week internship during Summer 2027. - Experience coding in Go, C++, Python, Java, or C#.

Preferred Qualifications - Intent to return to your degree program after the internship. - Strong fundamentals in systems, distributed computing, or software engineering — shown through internships, work, research, competitions, or projects. - Curiosity about large-scale or AI/ML infrastructure; exposure to Linux, containers, or Kubernetes is a plus but not required. - High creativity and quick problem-solving.