ML Platform Intern: Build Scalable Serving & Orchestration

Pangle; San Jose, Northern (CA, KY); Hybrid; USD 20,000 - 33,000; Part time

Job summary

ByteDance is seeking an intern for the Data-AML-Engine Orchestration team in San Jose to help build large-scale ML infrastructure powering TikTok and other products. You will work on orchestration, scheduling, and resource management systems that connect heterogeneous compute with production ML workloads across multi-cluster environments.

This internship offers hands-on experience, industry exposure, and opportunities to apply knowledge while building a strong foundation for personal and

Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, or related field.
• Proficiency in Go, C++, or Python with strong CS fundamentals.
• Familiarity with Linux and distributed systems concepts.
• Willingness to explore systems via code, metrics, logs, and profiling.
• Ability to define measurements and test hypotheses for system improvements.
• Demonstrated ownership and collaboration through projects or internships.

Responsibilities

• Design and build foundational orchestration capabilities for ML platforms (Kubernetes Operators, containers, job lifecycle).
• Develop multi-tenant resource and quota systems to improve GPU utilization and cost efficiency.
• Build lifecycle orchestration for online model serving with deployment, upgrades, and autoscaling.
• Create serving orchestration and traffic management for disaggregated clusters, with QoS/SLA focus.

Skills

Go

C++

Python

Linux

Distributed systems

Algorithms

Problem solving

Ownership

Education

Bachelor's/Master's in CS or related field

Tools

Kubernetes

Container runtimes

Volcano

OpenKruise

vLLM

KServe

Ray Serve

Job description

ByteDance is seeking an intern for the Data-AML-Engine Orchestration team in San Jose to help build large-scale ML infrastructure powering TikTok and other products. You will work on orchestration, scheduling, and resource management systems that connect heterogeneous compute with production ML workloads across multi-cluster environments.

This internship offers hands-on experience, industry exposure, and opportunities to apply knowledge while building a strong foundation for personal and