Top Tech Jobs & Startup Jobs

Design and develop high-performance ASIC RTL for Cerebras wafer-scale AI processors. Responsibilities include functional specification, microarchitecture, RTL development, synthesis, front-end and third-party IP integration, PPA optimization, verification and DFT collaboration, silicon bring-up debugging, and coordination with software, systems, physical design teams, and external vendors.

Design, configure, develop, test, deploy, and support scalable NetSuite ERP solutions. Translate Finance, Supply Chain, manufacturing, and operations requirements into workflows, integrations, automations, and business processes. Own solution architecture, technical discovery, production support, Agile delivery, testing, security, monitoring, and operational handoff. Partner with cross-functional stakeholders to deliver reliable integrations with adjacent enterprise platforms while reducing customization and maintaining strong controls.

Build and evolve production ML inference APIs and serving infrastructure across GPU and Cerebras accelerator backends. Responsibilities include API design, model integration, request routing, disaggregated prefill/decode coordination, performance optimization, correctness validation, observability, testing, SDKs, and developer tooling. The role requires close collaboration across compiler, runtime, cloud, product, and customer-facing teams to deliver reliable, compatible, scalable inference capabilities.

Designs deployment-ready AI data center infrastructure, including rack layouts, equipment placement, bills of materials, power allocations, port maps, and cabling. Adapts cluster designs to site constraints, validates integrated compute, storage, networking, and power systems, supports deployment readiness, resolves integration issues, and automates design and validation workflows using scripts and reusable tools.

Designs and implements security controls for on-premises and cloud distributed systems, including bare-metal, virtualized, and Kubernetes environments. Responsibilities include defining security requirements, hardening cluster infrastructure, developing threat models, identifying security gaps, partnering with engineering teams, embedding secure design practices, and documenting security posture for technical and nontechnical audiences.

Secure Cerebras’s software supply chain from source code through deployed artifacts. Responsibilities include defining and implementing SLSA-based build security requirements, hardening CI/CD pipelines, developing threat models, assessing trust boundaries, partnering with platform and infrastructure teams, modernizing legacy build environments, and documenting security strategy for technical and nontechnical audiences.

Define multi-generation scale-up and scale-out network architectures for AI accelerator platforms. Translate application and system communication patterns into bandwidth, latency, reliability, and serviceability requirements. Specify fabric topologies, protocols, routing, switching, buffering, flow control, and fault containment. Evaluate standards-based versus custom designs using performance models, simulations, prototypes, and lab data. Lead architecture specifications, design reviews, implementation decisions, bring-up, and qualification across hardware and software teams.

Lead performance modeling and architecture analysis for next-generation AI accelerators. Build analytical, simulation-based, and trace-driven models; analyze AI workloads and hardware bottlenecks; evaluate architectural features; validate models against RTL, emulation, and silicon data; and provide recommendations that influence hardware and software roadmaps. Partner with architecture, compiler, kernel, runtime, and systems teams to improve latency, throughput, utilization, and energy efficiency.

Leads end-to-end technical programs for AI compute systems and data center deployments. Owns engineering improvement schedules, hardware change implementation, software integration, validation, risk mitigation, and cost management. Coordinates product, engineering, manufacturing, supply chain, procurement, and software teams while presenting program status and risks to senior leadership. Develops scalable processes and ensures hardware and software deliverables meet performance, budget, and schedule objectives.

Own and scale major areas of Cerebras’s Developer Console, including billing, usage tracking, quotas, request logs, and metrics. Design frontend systems and backend services using Next.js, TypeScript, GraphQL, Postgres, and Redis. Make architectural decisions across APIs, data models, distributed systems, and real-time processing. Lead projects from conception through production, improve reliability and observability, partner with product and design, and mentor engineers.