9 months ago
Palo Alto, CA, USAIntern
Responsibilities
- Build and maintain cloud-native services and tooling supporting the GPU cloud platform.
- Use Kubernetes to help manage, schedule, and optimize GPU workloads across clusters.
- Design and implement APIs, automation scripts, and internal tooling to improve platform reliability and developer experience.
- Contribute to infrastructure-as-code, CI/CD pipelines, and deployment automation.
- Write documented, tested code and participate in code reviews.
- Collaborate with infrastructure, product, and research teams to ship features.
- Use AI-assisted coding tools such as GitHub Copilot, Cursor IDE, and ChatGPT.
Requirements
- Currently pursuing a B.S. or M.S. in Computer Science, Engineering, Mathematics, or a related field.
- Strong programming skills in Go, Python, C/C++, or similar languages.
- Strong mathematics and computer science fundamentals, including algorithms, data structures, discrete mathematics, or systems.
- Hands-on experience with Kubernetes, Docker, or cloud-native technologies.
- Familiarity with GCP, AWS, or Azure and cloud infrastructure concepts.
- Experience with Git and GitHub and comfort working in Linux/Unix environments.
- Ability to communicate complex technical ideas clearly in writing and code.
- Curiosity, self-direction, and enthusiasm for an early-stage environment.
- Experience with competitive programming, research, or independent technical projects is expected or relevant.
- Preferred experience includes GPU infrastructure, NVIDIA tooling, AI/ML workload orchestration, CNI plugins, network policy, multi-tenant Kubernetes, Prometheus, Grafana, alerting pipelines, distributed systems, NFS, object storage, high-speed networking, or open-source cloud-native projects.
Benefits
- Competitive internship stipend commensurate with experience.
- Hands-on exposure to GPU cloud infrastructure and AI systems.
- Mentorship from senior engineers with deep AI infrastructure expertise.
- Potential conversion to a full-time role for exceptional interns.
- Hybrid schedule with 3 days in the Palo Alto office and 2 days working from home.
Tech Stack
About Zettabyte
Zettabyte builds Zetta-ERP, a SaaS and white‑label platform for private universities that manages the student and academic lifecycle end to end. It also develops software to deploy, manage, and optimize large‑scale GPU clusters for enterprises and governments, working with hardware supply-chain partners like Foxconn, Wistron, and Pegatron. Founded in 2016 and headquartered in Singapore, the company is privately held and serves higher‑education institutions globally.