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AI Inference Core - Software Integration Engineer

Cerebras

United States and CanadaOn-siteFullTime

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. About the Role We are looking for a Software Integration Ninja to join the AI Inference Core team at Cerebras. This team sits at the intersection of AI infrastructure, distributed systems, compilers, runtimes, kernels, and hardware/software co-design. The Innovation Engine for Inference Core — turning ideas into reality. You will help take ambitious ideas from concept to working reality across the Cerebras inference stack. You will integrate and validate cross-component projects of high complexity, often on accelerated timelines, and work directly with engineers across AI, runtime, compiler, kernel, systems, and hardware teams. A Special Task Force, Not a Typical Engineering Role Zero-to-one mission: Take incomplete ideas and early prototypes all the way to working, validated capabilities. Cross-stack complexity: Move across AI frameworks, runtime, compiler, kernels, distributed systems, infrastructure, and hardware—not just one component or codebase. Accelerated and dynamic cadence: Expect focused daily syncs, rapidly changing priorities, and periods of intense integration work. This is not a role for engineers seeking strictly regular, predictable work hours. Comfortable on the hot seat: Take ownership when the path is unclear, make sound decisions with incomplete information, a

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