Jobs at Cerebras Systems Inc.

Early-career SDET on Release Integration Testing for Cerebras AI Inference Core. Write automation and tests across the AI stack, triage cross-stack failures, maintain branch stability, collect qualification evidence, and collaborate with feature and infra teams to prepare features for production release.

Own manufacturing test programs from new product introduction through qualification, production ramp, and sustaining. Build schedules, manage dependencies and risks, coordinate engineering, manufacturing, quality, and external partners, and oversee qualification-to-production handoffs. Track yield, test time, throughput, and capacity while ensuring test hardware and software are ready for high-volume production.

Lead end-to-end program schedules for hardware engineering improvements and wafer-scale supercomputer deployments. Coordinate product, electrical/system engineering, manufacturing, supply chain, and system software to define requirements, mitigate technical risks, manage materials and validation plans, control costs, implement process improvements, and report program status and operational risks to senior leadership.

Lead end-to-end bring-up of ML frameworks and models on Cerebras CSX systems, spanning model translation, compiler lowering, runtime integration, debugging performance/numerical issues, and prototyping tooling or API improvements to accelerate future deployments.

Design and develop software to automate bare-metal configuration, orchestration, scheduling, and job placement for large wafer-scale clusters. Build upgrade/patch workflows, monitoring, HA failure handling, visualization and alerting, and user/admin tools. Ensure on-premise and cloud deployment support and develop tests and debugging tools for distributed systems.

Develop, implement, and sustain manufacturing test automation from PCBA to system level. Build GUIs and web interfaces, work with contract manufacturers to deploy test infrastructure, reporting portals, and traceability. Troubleshoot test software and hardware defects and support manufacturing site setups.

Design and architect front-end datacenter and interconnect fabrics for AI/HPC clusters, prototype and productionize new network designs, automate deployment and validation (Python/Ansible), operate SRE-grade telemetry and observability (gNMI, Prometheus, Grafana), debug host-NIC-fabric performance (RoCEv2, PFC/DCQCN, ECMP), lead multi-team projects, and collaborate with vendors and standards bodies to ensure network reliability.

Leads warehouse operations, inventory control, 3PL performance, reverse logistics, and inventory governance across multiple sites and partners. Owns cycle counts, transaction accuracy, ERP/WMS discipline, exception resolution, SOX readiness, audit controls, and process scalability. Partners with Finance, Manufacturing, Logistics, Quality, Systems, and external providers to improve inventory visibility, reduce discrepancies and write-offs, strengthen operational controls, and support manufacturing continuity.

Leads enterprise business-systems analysis across Finance, Supply Chain, People, Legal, and other functions. Partners with business and technical teams to map processes, define requirements, develop roadmaps, evaluate solutions, manage testing and releases, improve controls, support vendors, and drive adoption. The role also establishes business-analysis standards, resolves production issues, and identifies automation and AI opportunities while ensuring scalability, auditability, security, and data quality.

Leads the company’s SOX compliance program and establishes its Internal Audit function. Responsibilities include risk assessments, control documentation and testing, deficiency remediation, enterprise risk management, audit planning, cybersecurity and operational risk reviews, external auditor coordination, Audit Committee reporting, and building an internal audit team. The role supports public-company compliance and requires executive-level leadership across Finance, IT, Legal, Security, Engineering, and Operations.

Manage global general ledger operations and monthly, quarterly, and annual financial close processes under U.S. GAAP. Prepare journal entries, reconciliations, variance analyses, audit schedules, and external reporting support. Develop accounting frameworks for international entities, strengthen policies and internal controls, coordinate with service providers and auditors, support sales and use tax filings, and collaborate cross-functionally to ensure accurate and timely financial information.

Design and deliver production FPGA solutions for chassis-to-wafer IO including RoCE v2/RDMA network interfaces, switching fabric, and serial IO. Develop RTL, produce bitstreams, optimize bandwidth and latency, debug large AI cluster networking, coordinate board bringup, and lead cross-functional projects with DV, embedded software, and architecture teams.

Lead development and automation of tests for large-scale AI clusters to ensure extreme reliability and security. Design test strategies for distributed ML training/inference, automate cluster tests (HA, failures, performance, stress, security), qualify networking and security components, and validate hardware and observability stacks.

Lead architecture and evolution of enterprise, data center, and cloud networks for hyperscale AI; design secure, high-performance fabrics (spine/leaf, RDMA); build AI-agent review frameworks; implement segmented zero-trust network designs; set resiliency, observability, and capacity standards; mentor global engineers and guide cross-functional initiatives.

Design, build, and operate firewall, segmentation, and zero-trust controls across data center, corporate, and cloud networks. Implement infrastructure-as-code for policy and CI/CD deployment, manage lifecycle and rule hygiene, build network detection capabilities, operate VPN/remote access patterns, and document architecture and runbooks while partnering with Network Engineering and Security Operations.

Join IT & Security to secure and scale enterprise IT, cloud, network, and infrastructure; build automation and tooling; support detection, response, and vulnerability management; improve identity, endpoint, and systems security; and partner cross-functionally to develop processes that enable secure, reliable, and scalable AI workloads.

Build and maintain customer-facing AI cloud frontends (inference, training, admin consoles, and APIs). Design responsive, high-reliability interfaces to handle high traffic, using modern web frameworks and best practices. Collaborate on architecture, ensure production-grade quality, and thrive in ambiguous, fast-changing environments while sharing knowledge and communicating clearly.

Lead engineering for end-to-end security of large-scale AI clusters. Define and execute cluster security roadmap, build detection/response tooling, collaborate with corporate security and customers, and hire/lead an engineering team to deliver multi-tenant, network- and access-controlled secure cluster solutions across hardware, networking, and software layers.

Operate, monitor, and optimize large-scale AI compute clusters built on the Wafer-Scale Engine. Develop and own software for cluster operations (monitoring, automation, APIs, dashboards), deploy and debug Docker-based services, troubleshoot distributed systems, maximize compute capacity, and participate in a 24/7 on-call rotation while collaborating cross-functionally to improve operational visibility and reliability.

Lead design verification efforts for Cerebras AI chips: develop verification strategies, create reusable testbenches and environments, implement tests, run regressions, gather coverage, debug across simulation/emulation/silicon, and collaborate with architecture, RTL, physical design, firmware, and validation teams to improve verification infrastructure and methodology.