Infrastructure Intern

About the role

This internship sits at the intersection of platform engineering, cloud infrastructure, security, and AI systems. You will work directly with experienced infrastructure engineers on projects that support Meshy’s rapidly growing AI platform and GPU-based workloads.

This is a hands-on engineering internship where you will contribute to real production-impacting infrastructure initiatives across cloud platforms, developer tooling, observability, automation, and internal platform systems.

You’ll Gain Exposure To:

• GPU infrastructure and AI platform engineering
• Kubernetes and cloud-native systems
• Infrastructure as Code (Terraform)
• CI/CD and deployment workflows
• Security and compliance tooling
• Reliability and scalability challenges in AI systems

What Projects You’ll Work On

Rebuilding and improving staging environments in non-production infrastructure using Terraform and cloud-native tooling

Contributing to internal infrastructure platform initiatives across reliability, automation, observability, and developer experience

Supporting Kubernetes- and cloud-based infrastructure used for AI training and inference workloads

Helping evaluate and improve security and compliance tooling and processes

Building internal tooling and automation to improve engineering productivity and operational efficiency

Collaborating with infrastructure, research, and product engineering teams on high-priority platform initiatives

Qualifications

• Currently pursuing a Bachelor’s, Master’s, or PhD in Computer Science, Software Engineering, or a related technical field
• Strong coding skills in Python, Go, or similar backend languages
• Familiarity with Linux systems and cloud platforms (AWS, GCP, or Azure)
• Exposure to Kubernetes, Docker, Terraform, or Infrastructure as Code concepts
• Interest in infrastructure engineering, distributed systems, DevOps, SRE, or AI infrastructure
• Strong curiosity, ownership mindset, and willingness to learn quickly in a fast-paced startup environment

Nice to have

• Experience with personal projects, hackathons, open-source contributions, or research projects
• Familiarity with CI/CD pipelines, observability tooling, or cloud security concepts
• Exposure to GPU infrastructure, ML systems, or AI platforms
• Experience deploying services using Kubernetes or Docker