Full-Time
Cloud Native Engineer
Zettabyte
11-50 employees
High-performance GPU cloud IaaS provider
No salary listed
No H1B Sponsorship
Palo Alto, CA, USA
Hybrid
Three days in the office and two days working from home per week; must be located in Palo Alto.
 Software Engineering (1) |
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- At least 7 years of software engineering experience focused on distributed systems and cloud native technologies.
- Strong proficiency in Go, including a deep understanding of concurrency patterns and standard libraries.
- Familiarity with Python or other backend languages for polyglot development environments.
- Hands-on Kubernetes experience, including development, deployment, and maintenance of production clusters.
- Solid understanding of microservices architecture design patterns and implementation best practices.
- Experience with containerization technologies such as Docker and containerd, including container runtime optimization.
- Ability to independently design and implement complex system components.
- Experience using AI-assisted coding tools and willingness to integrate them into the development workflow.
- Authorization to work in the United States without visa sponsorship.
- Design and develop microservices using Go for the AI cloud platform's core functionality.
- Build and maintain Kubernetes-based infrastructure for container orchestration and workload management.
- Implement and optimize cloud native solutions for scalability, reliability, and performance.
- Contribute to code reviews, technical documentation, and knowledge sharing within the engineering team.
- Explore and integrate emerging cloud native technologies such as Volcano, Prometheus, and service mesh solutions.
- Design distributed systems architecture for high-availability AI workload processing.
- Collaborate with DevOps and site reliability engineering teams to ensure production reliability and monitoring.
- Leverage AI-assisted coding tools such as GitHub Copilot, ChatGPT, and Cursor IDE to improve productivity and code quality.
- Familiarity with cloud native ecosystem tools such as Prometheus, Grafana, Volcano, or service mesh technologies.
- Open source contributions to cloud native projects, including Kubernetes and the Cloud Native Computing Foundation ecosystem.
- Experience with large-scale Kubernetes cluster operations and troubleshooting in production environments.
- Knowledge of microservices architecture patterns including circuit breakers, service discovery, and distributed tracing.
Zettabyte provides GPU cloud infrastructure as a service by building and operating AI data centers with on-demand NVIDIA GPUs (H100/A100). Its Zsuite software, including Zware, orchestrates and optimizes AI workloads across multiple GPUs, servers, and data centers, automating resource management and scheduling for AI training and inference. It differentiates itself with turnkey enterprise solutions, energy-efficient liquid-cooled data centers (a first in Taiwan), and partnerships with manufacturers and data-center capacity providers. Its goal is to help customers accelerate AI initiatives worldwide by delivering easy access to powerful compute and efficient workload management.
Company Size
11-50
Company Stage
N/A
Total Funding
N/A
Headquarters
Taipei, Taiwan
Founded
2024
Get referred to Zettabyte
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Simplify's Take
What believers are saying
- August 13, 2026 MaaS adds open-weight models through one API on zCLOUD.
- January 28, 2026 Headline Asia funding accelerates Japan expansion and TITAN rollout.
- July 7, 2026 ITRI collaboration strengthens Taiwan sovereign-AI positioning and university adoption.
What critics are saying
- Nebius, CoreWeave, and Lambda compress GPU pricing and margin through 2026.
- NVIDIA supply dependence makes Zettabyte hostage to H200 and B300 allocation cycles.
- If zCLOUD utilization slips, capital-intensive data centers and software become an existential drag.
What makes Zettabyte unique
- Zettabyte pairs zSUITE orchestration software with owned AI data centers and managed GPU cloud.
- David Ku and Kenneth Tai combine Microsoft AI, Acer, and Taiwan hardware relationships.
- Zettabyte unifies 40-plus hardware providers across H100, H200, B200, and B300 fleets.
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Growth & Insights and Company News
6 month growth
↓ -16%1 year growth
↓ -16%2 year growth
↓ -16%Zettabyte brings open source AI models to cloud through one API. August 17, 2026 Zettabyte has launched a managed cloud service that gives organisations API access to open-source and open-weight AI models, reducing the infrastructure needed to deploy and run them. Zettabyte has launched Model-as-a-Service (MaaS) on zCLOUD, turning access to open-source and open-weight AI models into an on-demand cloud service through a single API. The service gives organisations access to models including Kimi, GLM, Llama, GPT-OSS, Gemma, and Qwen without requiring them to independently deploy and manage each model. The models run on Zettabyte's NVIDIA H100, H200, B200, and B300 GPUs. Teams can call them through APIs without sourcing, installing, or tuning the models themselves. Organisations requiring greater control can instead rent raw GPU capacity on zCLOUD and run their own models. NVIDIA H100 capacity is available immediately, starting at US$1.99 per GPU-hour depending on requirements and scale. zCLOUD targets 99.5% uptime, while reserved clusters are designed for deployment within six hours of confirmed requirements. Zettabyte offers short-term GPU capacity, reserved clusters for sustained training and inference, and private cloud deployments for procurement, security, or regional requirements. "AI computing will be everywhere, from hyperscale data centers to the edge. The supporting AI infrastructure and software must be compatible, resilient, and agile. zCLOUD was built to deliver Model-as-a-Service, bringing more than 40 hardware providers together and managing the underlying AI infrastructure through our zSUITE full stack," said Dr. David Ku, Technology Leader at Zettabyte and former Corporate Vice President and CTO of AI at Microsoft. The service creates a middle ground between proprietary AI APIs and self-hosted open models, giving organisations a managed way to adopt open AI without first building the underlying infrastructure.
Zettabyte has launched Model-as-a-Service on zCLOUD, its GPU cloud platform. The service hosts open-weight and open-source models including Kimi, GLM, Llama, GPT-OSS, Gemma, and Qwen, making them accessible through a single API. Teams can access models running on Zettabyte's NVIDIA H100, H200, B200, and B300 GPUs without needing to source, install, or tune models themselves. NVIDIA H100 is available from $1.99 per GPU-hour. The platform offers three access options: short-term capacity with no long-term commitment, reserved clusters under term commitments, and private cloud for custom deployments. zCLOUD operates with a 99.5% uptime target. Dr David Ku, technology leader at Zettabyte and former corporate vice president and CTO of AI at Microsoft, said the platform brings together more than 40 hardware providers.
AI demand explodes over 300-fold. Zettabyte makes the case for quality compute and Taiwan's Sovereign AI Future. July 7, 2026 TAIPEI, July 7, 2026 /PRNewswire/ - As global consumption for AI computing tokens accelerates at unprecedented speed, Zettabyte, a global AI computing company, is using the occasion to argue that compute should be judged by the quality of the useful work it delivers, not by hardware specifications and hourly price alone. Zettabyte made its case for quality compute for sovereign computing standards at the AI Server Supply Chain Seminar convened by the Industrial Technology Research Institute (ITRI) in Taipei. Founded in 1973, ITRI has played a vital role in transforming Taiwan's semiconductor industry. Over the years, ITRI has incubated hundreds of startups and spinoffs, including well-known companies such as United Microelectronics Corporation (UMC) and Taiwan Semiconductor Manufacturing Company (TSMC). "Taiwan's strength in semiconductors and AI hardware is well established. Developing rigorous standards for how compute is measured is a logical next step, and the kind of work ITRI is positioned to support," said Stephen Su, Senior Vice President, ITRI. Against this backdrop, Zettabyte set out its core argument at the seminar it co-organized with ITRI: a cluster should be judged by the useful work it delivers, not by the amount of hardware it contains. "The AI industry has measured infrastructure primarily through two metrics: GPU count and hourly rental cost. Yet neither metric answers the core question that matters most to customers," said Jeff Lin, Executive Director of Zettabyte. "Paying customers want to know how much 'useful' AI is being produced by the GPUs, and to be able to reliably measure this. Recent disputes highlight a long-growing disconnect between consumer expectations and the actual cost of providing AI inference." zSUITE measures how much useful compute a GPU cluster actually delivers, giving operators visibility into the reliability and efficiency gaps that drive up to 15 percent of total cost. Investing in Taiwan's Sovereign AI Future Zettabyte is actively advancing software licensing for its zSUITE platform for Taiwan sovereign use, and is rolling out collaboration with ITRI and selected leading universities across Taiwan with AI programs and research labs. The company views the program as an investment in the next generation of AI infrastructure talent and a contribution to Taiwan's continued leadership in the global AI ecosystem. By putting the same measurement tools it uses in production into the hands of Taiwan's research institutes and universities, Zettabyte aims to help build the local expertise on which sovereign AI infrastructure depends. About Zettabyte Zettabyte is a global AI computing company focused on delivering measurable high-quality compute. Through its zSUITE platform, the company enables organizations to visualize data, computing, and goodput to improve reliability, readiness, observability, cost transparency, and energy efficiency across AI infrastructure environments. About ITRI ITRI is a world-leading applied technology research institute with more than 6,500 employees. Its mission is to drive industrial development, create economic value, and enhance social well-being through technology R&D.
Zettabyte and LiteOn have announced a research and development collaboration to evaluate a distributed edge AI inferencing platform called the Ultra Edge Pod, deployed at cell tower locations. The project aims to bring AI inference workloads closer to users through Mobile Edge Compute platforms, reducing latency and enabling AI readiness in countries without mature data centre infrastructure. LiteOn will provide power, cooling and physical infrastructure, whilst Zettabyte will deliver software for GPU scheduling, orchestration and remote operations. The deployment will demonstrate how integrated infrastructure and software can enable reliable, low-cost AI inference in distributed environments with real-world power and thermal constraints. The platform is designed to support low-latency, location-aware AI inference workloads operating closer to mobile users and radio access networks.
/PRNewswire/ -- Zettabyte, an AI computing company, today announced a strategic investment from Headline Asia. The investment will support Zettabyte's...