Cerebras · San Francisco
Software EngineeringSoftware Engineering RemoteFullTimeposted 6d ago
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.
Responsibilities:
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, balancing cost, performance, scalability, and reliability.
Troubleshoot complex build failures, pipeline bottlenecks, and infrastructure issues, driving root-cause analysis and implementing durable fixes.
Design and drive improvements to internal build infrastructure, test infrastructure, developer tooling, and automation that increase developer velocity and engineering productivity.
Identify systemic bottlenecks across developer workflows and lead architectural improvements to developer infrastructure.
Contribute to the company’s efforts around AI tooling to improve engineering productivity and automate repetitive workflows.
Provide technical leadership across projects, influence engineering standards, and mentor other engineers within the Developer Productivity organization.
Participate in on-call and incident response for Developer Productivity systems and services.
Skills & Qualifications
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.
Experience with containerization and container orchestration, with Kubernetes preferred.
Strong troubleshooting skills and the ability to debug complex distributed systems and infrastructure issues.
Demonstrated experience leading technical initiatives across multiple teams and driving improvements to developer infrastructure at organizational scale.
Ability to identify architectural bottlenecks, evaluate tradeoffs, and drive long-term improvements rather than only addressing operational issues.
Experience operating production systems and participating in on-call, incident response, and postmortem processes.
Preferred Skills & Qualifications
Experience with infrastructure-as-code tools and practices.
Proficiency in Python, Go, Shell, or another language used for infrastructure automation and developer tooling.
Experience with build systems, build graph optimization, or large-scale build infrastructure.
Experience with observability practices including monitoring, logging, alerting, and performance analysis.
Experience building internal developer platforms, self-service tooling, or developer-facing infrastructure.
Experience applying AI/LLM tooling to engineering workflows or developer productivity.
BS/MS in Computer Science or a related field, or equivalent practical experience.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
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