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AI supercomputers and fast inference platform for enterprises

Founder and CEO

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Cerebras shares fall as UBS cuts price target

CBRS SHAREHOLDER INVESTIGATION: SueWallSt Notifies Investors of Potential Securities Claims Involving Cerebras Systems

Cerebras Systems Investigation Notice: Levi & Korsinsky Notifies Investors of Pending Investigation Into Cerebras Systems (CBRS)

Oracle expands AI chip offerings with Google, Nvidia, and Cerebras

AI Engineer, Developer Relations

Cerebras is hiring an AI Engineer for its Developer Relations team. The role builds and evaluates AI prototypes that showcase fast inference, optimizes model workflows, and creates technical content and developer education based on hands-on experimentation.

Developer Relations

Senior Software Engineer, ML API – AI Inference

Cerebras is hiring a Senior Software Engineer to build and evolve the ML API layer for its disaggregated AI inference systems. The role owns inference API, model integration, and request-routing features, delivering reliable, consistent serving across models and accelerator backends.

Staff Software Engineer, Observability

Cerebras builds AI hardware and systems. The Staff Software Engineer, Observability will set the architecture and roadmap for its observability platform, build telemetry pipelines at scale, and improve reliability and developer experience across hardware and software systems.

Senior Backend Engineer, Inference Cloud

Cerebras is hiring a Senior Backend Engineer to build and scale services powering Cerebras Inference Cloud, including the Developer Console and backend systems used to operate inference workloads. The role owns core cloud capabilities and takes them from architecture through production operation in partnership with frontend, infrastructure, inference, and product teams.

Cloud Infrastructure Engineer

Cerebras Systems builds advanced AI chip infrastructure designed to accelerate AI training and inference. The Cloud Infrastructure Engineer will design, build, and operate secure, scalable cloud infrastructure and identity platforms across AWS and company data centers, while developing automation, security controls, and infrastructure-as-code solutions. The role also supports production systems, incident response, and secure-by-design initiatives across engineering and security teams.

Staff Software Engineer, GPU Inference

Cerebras is hiring a Staff Software Engineer to productionize and optimize its GPU inference serving stack. The role spans custom inference APIs, vLLM, AMD ROCm software, and rack-scale GPU infrastructure, with a focus on reliability, numerical correctness, observability, and performance.

Senior Cloud Infrastructure Engineer

Cerebras is seeking a Senior Cloud Infrastructure Engineer to design, build, and operate the AWS infrastructure powering its products and platform. The role focuses on scalable, reliable, secure cloud systems, infrastructure as code, and partnering with engineering teams to maintain production infrastructure as the company scales.

Senior SDET, Release Integration Testing - AI Inference Core

Cerebras is hiring a Senior SDET for Release Integration Testing within AI Inference Core. The role develops test automation, validates complex inference systems across software and hardware layers, investigates failures, and improves release quality and reliability.

AI Inference Core - Senior SDET, Release Integration Testing

DevX Technical Writer

Cerebras builds AI hardware and systems. The DevX Technical Writer researches AI hardware, software, and infrastructure, tests technical claims through demos and benchmarks, and creates clear, evidence-based content for developers and the broader industry.

ML Runtime and Kernel Engineer - Core ML

Cerebras Systems builds AI-focused wafer-scale computing hardware and platforms. The Core ML team is seeking an engineer to bridge machine learning research and efficient execution on Cerebras systems by developing runtime components and high-performance kernels. The role involves implementing algorithms, diagnosing performance bottlenecks, and delivering robust, high-performance ML capabilities across frameworks, compilers, runtimes, and low-level kernels.