AI Infrastructure Intern: Scheduler & Compute Efficiency

Iaas Lc; Seattle (WA); On-site; USD 25,000 - 36,000; Part time

Job summary

Iaas Lc in Seattle, WA is offering a 12-week internship focused on building an AI-driven scheduler and improving hardware efficiency. You will work on a real project, contribute to workload placement, and help automate self-management with AI-agent-assisted tools.

We welcome undergrad or master's students in Computer Science, with experience in Go, C++, Python, Java, or C#, and an interest in distributed systems and Linux/Kubernetes.

Qualifications

• Currently pursuing an Undergraduate or Master’s degree in Computer Science or a related discipline.
• Available for a 12-week internship during Summer 2027.
• Experience coding in Go, C++, Python, Java, or C#.
• Intent to return to your degree program after the internship.
• Strong fundamentals in systems, distributed computing, or software engineering.
• 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 skills.

Responsibilities

• Work on one focused, real project such as improving the AI-driven scheduler for workload placement and balancing.
• Explore methods to increase efficiency in hardware usage, including compute, memory, or power optimization.
• Develop tools to enhance platform reliability and enable AI-agent-assisted automation for self-management.

Skills

Go

C++

Python

Java

C#

Education

Undergraduate or Master’s degree in Computer Science

Tools

Linux

Containers

Kubernetes

Job description

Iaas Lc in Seattle, WA is offering a 12-week internship focused on building an AI-driven scheduler and improving hardware efficiency. You will work on a real project, contribute to workload placement, and help automate self-management with AI-agent-assisted tools.

We welcome undergrad or master's students in Computer Science, with experience in Go, C++, Python, Java, or C#, and an interest in distributed systems and Linux/Kubernetes.