ML Infra Intern: Build Scalable Orchestration

Pangle

San Jose, Northern (CA, KY)

Hybrid

USD 20,000 - 27,000

Full time

14 days+
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Job summary

ByteDance is offering an internship on the Data-AML-Engine Orchestration team in San Jose. You will help design and build large-scale ML infrastructure, focusing on orchestration, scheduling, and resource management for production workloads across heterogeneous compute platforms.

The program provides hands-on experience, industry exposure, and opportunities to engage in challenging real-world projects. Interns will gain practical experience, participate in learning programs and workshops, and

Qualifications

  • 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 data structures and algorithms.
  • Familiarity with Linux and fundamentals of OS, networks, concurrency, and distributed systems.
  • Strong hands-on and exploratory abilities with source code, metrics, logs, profiling, and experiments.
  • Systematic, quantitative problem solving with ability to measure and test improvements.

Responsibilities

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

Skills

Go
C++
Python
Linux
Distributed systems

Education

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

Tools

Kubernetes
Container runtimes

Job description

ByteDance is offering an internship on the Data-AML-Engine Orchestration team in San Jose. You will help design and build large-scale ML infrastructure, focusing on orchestration, scheduling, and resource management for production workloads across heterogeneous compute platforms.

The program provides hands-on experience, industry exposure, and opportunities to engage in challenging real-world projects. Interns will gain practical experience, participate in learning programs and workshops, and

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