Cerebras Systems develops the fastest AI computer, the CS-3, featuring the revolutionary WSE-3 chip, accelerating deep learning tasks by unprecedented orders of magnitude.
Sunnyvale, California
Cerebras Systems is the world's fastest AI inference. We are powering the future of generative AI. We’re a team of pioneering computer architects, deep learning researchers, and engineers building a new class of AI supercomputers from the ground up. Our flagship system, Cerebras CS-3, is powered by the Wafer Scale Engine 3—the world’s largest and fastest AI processor. CS-3s are effortlessly clustered to create the largest AI supercomputers on Earth, while abstracting away the complexity of traditional distributed computing. From sub-second inference speeds to breakthrough training performance, Cerebras makes it easier to build and deploy state-of-the-art AI—from proprietary enterprise models to open-source projects downloaded millions of times. Here’s what makes our platform different: 🔦 Sub-second reasoning – Instant intelligence and real-time responsiveness, even at massive scale ⚡ Blazing-fast inference – Up to 100x performance gains over traditional AI infrastructure 🧠 Agentic AI in action – Models that can plan, act, and adapt autonomously 🌍 Scalable infrastructure – Built to move from prototype to global deployment without friction Cerebras solutions are available in the Cerebras Cloud or on-prem, serving leading enterprises, research labs, and government agencies worldwide. 👉 Learn more: www.cerebras.ai Join us: https://cerebras.net/careers/
On-site · Toronto
Lead the architecture and design of the chassis-to-wafer IO path, focusing on RoCE v2 network interfaces and programmable switching fabrics. Optimize bandwidth and latency while producing production-ready bitstreams for large-scale AI clusters.
On-site · Canada
Develop and deliver electrical infrastructure designs for next-generation AI clusters, including utility service and power distribution. Coordinate with multidisciplinary teams and external vendors to validate designs and support commissioning activities.
Hybrid · Toronto
You will design, build, and maintain the GPU inference stack, ensuring high performance and reliability for large-scale AI workloads. Additionally, you will establish operational practices for the GPU fleet, including deployment, monitoring, and performance tuning across distributed systems.
Hybrid · Canada
Establish and lead the Release Integration Testing (RIT) strategy for AI Inference Core to ensure reliable production releases. The role involves designing test architecture, managing the inference-path readiness gate, and leading cross-stack validation from cloud to wafer.
Hybrid · Canada
Design and maintain CI/CD systems and Kubernetes-based platforms to support engineering workflows. Automate infrastructure changes and perform root-cause analysis to improve system reliability and scalability.
Hybrid · Canada
Lead the Inference Model Scaling organization to define the technical vision and roadmap for enabling foundation models on Cerebras hardware. Manage a globally distributed team responsible for ML model compilation, optimization, and high-performance kernel development.
Hybrid · Canada
Integrate, test, and validate the software stack powering the Cerebras AI platform across runtime, compiler, and hardware layers. Develop automated tests and tools to improve the reliability and quality of large-scale machine learning workloads.
Hybrid · Canada
Design and implement high-performance machine learning and linear algebra kernels for the Cerebras Wafer-Scale Engine. Collaborate with hardware and compiler engineers to optimize compute utilization and validate system performance.
On-site · Toronto
You will innovate and execute tests on cutting-edge AI infrastructure, defining optimized test strategies and methodologies. The role involves ensuring the reliability of large deployments and championing cluster security and performance.
Hybrid · Toronto
Innovate and execute automated tests to ensure 99.999% reliability for large-scale AI cluster deployments. Validate cluster software and hardware components including Kubernetes, wafer-scale accelerators, and high-speed interconnects.
On-site · Toronto
Participate in the bring-up and validation of next-generation AI hardware systems and supporting software infrastructure. Develop automation frameworks and diagnostic tools to debug complex system-level issues and improve observability.
On-site · Toronto
Develop and maintain C++ simulator infrastructure for next-generation Wafer-Scale Engine systems, focusing on functional and pipeline-accurate simulation. Collaborate with cross-functional teams to validate architectural behavior and improve internal engineering workflows.
On-site · Toronto
The role involves characterizing and optimizing the performance of AI models on Cerebras hardware to identify bottlenecks and improve efficiency. Responsibilities include building performance models and optimizing kernel microcode to enhance inference speed and throughput.
On-site · Toronto
Design and operate secure, scalable cloud infrastructure and identity platforms across AWS and private data centers. Implement identity lifecycle management and security controls for AI-powered systems using automation and infrastructure-as-code.
On-site · Toronto
Develop and maintain CICD pipelines and artifact lifecycle systems to ensure efficient build and release workflows. Provision and optimize cloud infrastructure while creating internal tooling to enhance developer velocity and engineering productivity.
On-site · Canada
Design and maintain test infrastructure to validate the Cerebras Inference Platform across cloud and hardware environments. Collaborate with development teams to debug complex issues in networking, orchestration, and distributed services to ensure production readiness.
Hybrid · Toronto
Lead the testing strategy and execution for AI/ML models, focusing on accuracy, fairness, and performance at scale for the ML API features team. Architect end-to-end test strategies and drive automation initiatives to improve engineering efficiency and product quality.
On-site · Vancouver
Lead infrastructure operations and deployment execution across Western Canada to ensure AI infrastructure meets uptime and reliability targets. Act as the primary interface with facility providers and manage local teams to execute HQ-driven requirements.
On-site · Canada
Design, build, and operate network security controls across data centers, corporate infrastructure, and AWS cloud environments. Own the lifecycle of firewalls and segmentation while automating security infrastructure as code.
On-site · Canada
The role involves hardening the foundational layers of AI compute platforms, including the Linux kernel, firmware, and secure boot processes. The engineer will conduct security reviews of low-level components and develop kernel-level monitoring to detect attacker behavior.
