Cerebras powers the world's fastest AI inference on the biggest wafer chip. Cerebras CS-4 delivers up to 30x faster inference than GPUs.
About the role
Design, build, and evolve CI/CD pipelines that support reliable and efficient build, test, and release workflows across the organization. Own and improve artifact lifecycle systems, including versioning, storage, distribution, dependency management, and reproducible builds at scale.
What they're looking for
- 7+ years of professional experience in software engineering, infrastructure engineering, DevOps, developer productivity, or a related area
- Deep hands-on experience with CI/CD systems and building or evolving automated build, test, and deployment infrastructure
- Experience with artifact repositories, software packaging, dependency management, and reproducible build concepts
- Experience with cloud computing platforms, with AWS preferred, and programmatic infrastructure provisioning
- Strong experience with distributed version control systems, code review workflows, branching strategies, and repository management
- Strong understanding of Linux/Unix systems, networking fundamentals, and scripting or programming for automation
More about this role
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Design, build, and evolve CI/CD pipelines that support reliable and efficient build, test, and release workflows across the organization.
Own and improve artifact lifecycle systems, including versioning, storage, distribution, dependency management, and reproducible builds at scale.
Partner with development teams to design and improve code review workflows, branching strategies, and automated integration processes.
Provision, monitor, and optimize cloud infrastructure supporting CI workloads,...
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