Software Automation Engineer- Systems
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About the Role
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include top 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.
Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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.
Role Overview
As a Software Engineer specializing in automation, you will play a key role in designing and delivering software solutions that improve operational efficiency and streamline business processes. You will develop automation frameworks, tools, and applications that reduce manual effort, enhance system reliability, and support scalable growth across the organization.
In this role, you will collaborate closely with cross functional teams—including engineers, analysts, and business stakeholders—to understand workflow challenges and identify opportunities for automation. Your work may involve building process automation systems, develop real-time monitoring and alerting capabilities, integrating disparate systems, and creating data driven solutions to optimize performance.
Your contributions will help eliminate bottlenecks, reduce operational costs, and enable teams to focus on higher value activities. Ideal candidates have strong software engineering fundamentals, experience with automation tools and scripting languages, and a passion for building efficient, reliable, and elegant solutions in a dynamic environment.
Key Responsibilities
- Define, develop and support software test automation and infrastructure
- Continuous improvement of test coverage, performance and speed
- Break down complex systems into testable sub blocks
- Play a vital role in raising the quality of software and identifying areas of risk
- Create an easy-to-use interface for operations to run automation workflows
- Cross-functional work across multiple teams to identify and root-cause improve processes
Skills and Qualifications
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