Cerebras Systems

Role Description Cerebras is building some of the most advanced AI systems on the planet. Behind that is a new class of data center—high-density, high-performance, and built at speed. We’re looking for a Technical Program Manager to drive execution across engineering, procurement, and construction (EPC). This is not a coordination role. This is an ownership role. Responsibilities - Own Delivery - Drive end-to-end Data Center Delivery execution across data center builds - Own schedule, scope, and cross-functional alignment - Ensure seamless execution from design to commissioning - Control the Schedule - Build and manage integrated EPC schedules - Drive critical path execution and recovery plans - Lead weekly execution reviews with contractors and internal teams - Connect the Dots - Align engineering, supply chain, construction, and commissioning - Eliminate gaps between design intent and field execution - Resolve technical interfaces (power, cooling, controls, network) - Drive Procurement - Track long-lead equipment - Ensure procurement stays ahead of construction - Mitigate supply chain risks early - Own Field Execution - Work directly with general contractors and trades - Resolve RFIs and field issues - Ensure execution matches design and schedule - Deliver RFS - Coordinate commissioning across systems - Drive readiness for Ready for Service (RFS) - Ensure sites are operational - Manage Risk - Identify risks early and drive mitigation - Maintain visibility into issues and blockers - Step in and solve problems - Communicate Clearly - Provide concise updates to leadership (build dashboards) - Escalate with solutions and trade-offs Qualifications - 8-15+ years in data center or mission-critical infrastructure delivery - Experience in EPC or owner-side delivery - Strong understanding of electrical and mechanical systems - Proven ability to deliver on aggressive schedules - Comfortable operating in ambiguity - Strong field presence and technical depth Benefits - Build a breakthrough AI platform beyond the constraints of the GPU. - Publish and open source their cutting-edge AI research. - Work on one of the fastest AI supercomputers in the world. - Enjoy job stability with startup vitality. - Our simple, non-corporate work culture that respects individual beliefs. Company Description Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

Role Description The Datacenter Portfolio & Vendor Management Lead will own the operational backbone of Cerebras' global datacenter program. This person partners closely with Engineering, Infrastructure, Finance, Legal, Procurement, Accounting, and Executive Leadership to manage strategic supplier relationships, commercial agreements, budgets, payment operations, and portfolio reporting. This is a highly cross-functional role requiring exceptional organizational skills, commercial judgment, and the ability to drive execution across multiple simultaneous infrastructure programs. Responsibilities - Portfolio Management - Own the centralized portfolio of global datacenter projects - Track capacity deployments, schedules, milestones, risks, and dependencies - Develop executive dashboards and portfolio health reporting - Coordinate planning across Engineering, Operations, Finance, and Supply Chain - Contract Management - Own lifecycle management of datacenter contracts - Coordinate contract negotiations with Legal and Procurement - Track key commercial terms, renewals, amendments, and obligations - Maintain repository of supplier agreements and commercial documentation - Vendor Management - Manage strategic relationships with: - Colocation providers - Construction partners - Power and utility providers - Network providers - Equipment vendors - Professional services partners - Track vendor performance against SLAs and KPIs - Drive quarterly business reviews - Resolve commercial escalations - Financial Operations - Track purchase commitments and contract values - Partner with Finance on forecasting and budget management - Coordinate invoice approvals and payment workflows - Monitor spend against approved budgets - Support capital expenditure planning - Program Operations - Build scalable operational processes for the rapidly growing datacenter organization - Drive governance reviews - Maintain risk registers - Coordinate executive reporting - Improve portfolio management tooling and reporting automation Qualifications - 8+ years managing complex infrastructure, construction, or technology programs - Experience managing large vendor portfolios - Strong contract administration experience - Budget ownership experience ($10M+ preferred) - Experience working with Finance and Legal organizations - Excellent project management skills - Ability to work across highly technical engineering organizations - Outstanding communication and executive presentation skills Preferred Qualifications - Experience with one or more: - Hyperscale datacenters - Cloud infrastructure - AI infrastructure - Colocation providers - Construction management - Critical facilities - Supply chain operations - ERP systems (Oracle, SAP, NetSuite) - Coupa - Jira - Smartsheet - Airtable - Tableau or Power BI Success in this Role Within your first year you will: - Build operational rigor across Cerebras' global datacenter portfolio - Improve visibility into project health and financial performance - Establish scalable vendor governance processes - Streamline contract and payment workflows - Enable infrastructure teams to execute faster by reducing operational overhead - Establish metrics of economic KPI’s in all leases in the portfolio (Contracted vs actual) Benefits - Build a breakthrough AI platform beyond the constraints of the GPU. - Publish and open source their cutting-edge AI research. - Work on one of the fastest AI supercomputers in the world. - Enjoy job stability with startup vitality. - Our simple, non-corporate work culture that respects individual beliefs. Company Description Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

• Define and own the architectural roadmap for Cerebras's enterprise, data center, and cloud network estate. • Co-author secure design and lifecycle management of high-performance data center networking — including spine/leaf, RDMA, and high-bandwidth fabrics supporting wafer-scale compute. • Build and maintain an AI-agent based analysis and review framework for network changes as well as self-improvement driven by observed network patterns and use cases. • Partner with Network Security to deliver segmented, zero-trust-aligned network designs across data center and corporate environments. • Set standards for resiliency, observability, and capacity planning across the global network • Mentor engineers across regions (US, Canada, Bangalore, and beyond), and serve as the senior technical voice on cross-functional network initiatives. • Stay ahead of emerging networking patterns relevant to AI infrastructure and translate them into actionable architecture decisions.

• Design and operate firewall, segmentation, and zero-trust controls across data center, corporate, and cloud (AWS) networks. • Build and maintain network security infrastructure as code — including firewall rules, policy automation, and CI/CD-driven deployment. • Lead network lifecycle management: design review, configuration baselines, change automation, and ongoing rule hygiene. • Build detection capabilities for network-based attacker behaviors and partner with the Detection & Response team on response playbooks. • Implement and operate network access controls including ZTNA, VPN, and remote access patterns. • Drive periodic firewall rule reviews, segmentation audits, and remediation campaigns to reduce risk and complexity. • Document network security architecture, controls, and operating procedures in clear runbooks.

• Define security architecture and build controls for AI platforms, training and inference workflows, model-serving systems, customer workloads, developer workflows, and agentic • Develop reusable AI and agent security patterns for identity, authorization, delegated authority, scoped tool access, MCPs, connectors, secrets, approvals, isolation, auditability, and • Design runtime controls that constrain execution, access, data exposure, model and tool interaction, and blast radius. • Build security capabilities as code using infrastructure as code, configuration as code, policy as code, GitOps, CI/CD, and automated validation. • Define secure development patterns for AI systems, agents, prompts, tools, models, policies, evaluations, releases, and rollback. • Automate security reviews, policy checks, evidence collection, control validation, and remediation • Instrument AI, agent, and platform activity with telemetry, traceability, policy decisions, audit logs, anomaly signals, and response workflows. • Lead hands-on security reviews and influence product, platform, infrastructure, and security architecture through practical design changes and reusable controls.

• Partner with platform, infrastructure, and hardware teams to embed security controls from physical hardware through runtime. • Design and implement security hardening across the Linux kernel, bootloader, firmware, and host OS layers of Cerebras compute platforms. • Drive secure boot, measured boot, and attestation strategies across our infrastructure, from the wafer-scale system to supporting host nodes. • Conduct deep security reviews of kernel modules, drivers, and low-level system components — identifying and remediating memory safety, privilege escalation, and isolation issues. • Develop kernel-level monitoring and telemetry (e.g., eBPF) to enable detection of low-level attacker behavior. • Stay ahead of emerging kernel CVEs, supply chain risks, and hardware-level threats — driving response and remediation across the fleet. • Document low-level security posture, threat models, and remediation playbooks in clear, accessible language.

• Own delivery of AI-optimized data center capacity (colo, build-to-suit, retrofits, and owned facilities) from pre-contract planning through operational readiness. • Deliver MW-scale infrastructure aligned to aggressive GPU/AI system deployment targets. • Drive clarity from ambiguity—translate high-level demand signals into executable delivery programs. • Decompose complex build programs into workstreams with clear owners, milestones, and deliverables. • Build integrated plans spanning real estate, power/energy, design, procurement, construction, and deployment. • Establish critical path visibility and aggressively manage schedule compression. • Orchestrate execution across real estate & site selection, power & energy strategy, data center design, supply chain & procurement, construction & commissioning, infrastructure deployment, networking, and security. • Identify and drive resolution of critical risks, constraints, and blockers. • Own and maintain program budgets, CapEx forecasts, and capital allocation narratives. • Partner with capacity planning, AI infrastructure, and finance teams to translate model demand into site-level capacity strategies. • Continuously optimize for time-to-capacity and cost-per-MW / cost-per-GPU deployed. • Drive E2E improvements in delivery through standardization, implementation of program tooling, and post-mortems.

Title: Design Verification Engineer Location: Sunnyvale, CA Job Description: 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. Key Responsibilities - Work with architects, designers, post-silicon, and software engineers, to ensure a high-quality design that works for silicon. - Develop and implement verification strategies, detailed tests, and coverage plans based on micro-architecture. - Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage. - Implement tests, manage regressions, gather coverage, and debug test failures. - Collaborate with cross-functional teams, including architecture, RTL design, physical design, firmware, and validation. - Analyze and debug complex issues across simulation, emulation, and silicon bring-up phases. - Continuously enhances verification infrastructure and flows to improve efficiency and quality. - Contribute to the evolution of the overall verification methodology and best practices across the organization. Skills and Qualifications - Advanced debugging and problem-solving skills. - Deep knowledge of SystemVerilog testbench, DPI, and UVM. - Excellent programming skills and knowledge of software engineering practices, including object-oriented design. - Experience developing scalable and portable testbenches and components. - Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, and gate-level simulations. - Proficient in scripting languages such as Python or Perl. - Good interpersonal skills and the ability to work as a standout colleague are a must. - Extremely self-motivated and eager to solve problems - 3+ years of Design Verification experience. Desired Skills and Qualifications - Knowledge of pipelined processor architecture. - BS or MS in Computer Science or Electrical Engineering. - 3+ years of hands-on Design Verification experience. The base salary range for this position is $120,000 to $240,000 annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications. We are open to remote candidates. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: - Build a breakthrough AI platform beyond the constraints of the GPU. - Publish and open source their cutting-edge AI research. - Work on one of the fastest AI supercomputers in the world. - Enjoy job stability with startup vitality. - Our simple, non-corporate work culture that respects individual beliefs. Read our blog: Five Reasons to Join Cerebras in 2026. Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Role Description Cerebras Systems Inc. has multiple openings for Member of Technical Staff (Software Engineer). - Implement infrastructure to support high-performance, low-latency inference service. - Deploy and configure Kubernetes services to ensure scalability and reliability of inference workloads. - Optimize resource allocation and auto-scaling policies to handle variable inference demand while minimizing operational costs. - Integrate inference services with containerized environments using Docker and Kubernetes for orchestration. - Ensure high availability and fault tolerance by implementing multi-region deployments and disaster recovery strategies. - Develop Python-based scripts and APIs to streamline data preprocessing, inference execution, and post-processing for real-time inference tasks. - Collaborate with machine learning engineers to validate inference accuracy and performance against functional and latency requirements. - Triage and resolve defects in the service by analyzing logs, metrics, and distributed traces. - Debug issues related to model deployment, container orchestration, or networking configurations, documenting steps to reproduce and root-cause defects. - Collaborate with cross-functional teams to address performance regressions, scalability issues, or integration failures in the inference pipeline. - Develop automated scripts to detect and mitigate common failure modes, improving system reliability. - Author detailed technical documentation for infrastructure configurations, inference workflows, and APIs, ensuring clarity for internal teams and external customers. - Work with product management and user experience teams to define requirements for inference service interfaces, including configuration, monitoring, and event logging. - Document and track defects, enhancements, and release notes using tools like Jira and Git, ensuring version control and traceability. - Participate in release planning and prioritization discussions to align infrastructure development with customer needs and business objectives. Qualifications - Master’s degree or foreign equivalent degree in Computer Science, or a related field. - 1 year of experience as Software Developer, Student/Intern (Software Developer), Member of Technical Staff (Software Engineer), Software Engineer, or a related occupation. - Employer accepts full-time or equivalent part-time experience gained before, during or after graduate studies. Requirements - Docker and Kubernetes - Java or C++ - ActiveMQ and Kafka - Python or Groovy - JavaScript or TypeScript - Linux - SQL, OracleDB, and Redis - Git Benefits - Build a breakthrough AI platform beyond the constraints of the GPU. - Publish and open source their cutting-edge AI research. - Work on one of the fastest AI supercomputers in the world. - Enjoy job stability with startup vitality. - Our simple, non-corporate work culture that respects individual beliefs. Company Description 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 Description Cerebras Systems Inc. has multiple openings for Sr. Technical Staff. - Post silicon validation of Cerebras Wafer Scale Engines. Test and debug issues on new silicon. - Test, analyze, and characterize high-speed serial interfaces to verify compliance with hardware specifications, record performance data, and recommend design modifications to optimize functionality. - Work with the silicon and operations team to test, bring-up and run burn-in on wafer scale systems. - Support manufacturing operations to utilize the wafer bring up flow. Perform wafer bring-ups, diagnose and debug problems encountered. - Develop and implement hardware to ensure compliance with design specifications. - Collaborate with hardware design engineers and system software engineers to review specifications and to recommend changes that will improve the quality and verifiability of the hardware designs. - Create and maintain automated regression test scripts, using Python and/or bash, that ensure that all tests are run and pass after each change to the design, testbench, tests, or reference model. - Work with system team members to diagnose system related failures. Understand the key system interfaces to FPGA’s, power and cooling, and apply that knowledge to the debug of silicon features. - Development of debug tools in Python to program and analyze the behavior of the Wafer Scale Engine. - Development of wafer bring up flow utilizing Python and shell scripts to capture the steps required to bring up a wafer in a logical easy to use flow. - Documentation of issues found, tools and flow. Qualifications - Master’s degree or foreign equivalent degree in Electrical Engineering, Computer Engineering, or a related field. - 3 years of experience as Application Engineer, Sr. Technical Staff, Hardware Engineer, or a related occupation. Requirements - Electrical Signal Integrity Analysis. - Hardware Bring-up & Debug. - Functional and Electrical characterization. - Test automation using scripting language. - High Speed Interfaces & Protocols including Ethernet, CPRI, or Interlaken. Benefits - Salary Range: $250,000.00 per year to $275,000.00 per year. - Telecommuting permitted. Company Description 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. - 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. - Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services.