Deploys, automates, troubleshoots, and maintains Linux compute and storage infrastructure, building repeatable systems and resolving complex issues to improve reliability and operational efficiency.
Develop and own test automation and release qualification for AI inference systems, validating cross-stack integrations, debugging complex failures, and improving regression stability and production reliability.
Own operational readiness, on-premises O&M, operator training and certification, and operational knowledge programs to help Cerebras infrastructure enter production and operate reliably across customer, partner, and company environments.
Drive data-informed supply chain programs by improving forecasting, inventory, procurement, and logistics processes, managing supplier risks, and presenting performance insights to leadership.
Own and support SEC reporting and technical accounting, preparing financial statements and disclosures, researching complex transactions and standards, strengthening reporting controls, and partnering with teams and external auditors.
Leads day-to-day operations of production infrastructure, building fleet-wide monitoring, incident response, maintenance, repair, and automation practices to restore systems quickly and scale reliable operations.
Bring up machine learning models on AI accelerators, develop MLIR lowering paths, validate numerical correctness, and optimize inference performance across models, compilers, kernels, and runtimes.
Research AI hardware and software, build demos and reproducible benchmarks, and turn verified findings into clear technical content that helps developers understand system performance, tradeoffs, and industry developments.
Research AI hardware and software, test technical claims with demos and reproducible benchmarks, and publish evidence-based analysis that explains system tradeoffs and their significance to developers and the industry.
Leads the Developer Relations vision, team, and roadmap while building technical demos and educational content that help developers adopt Cerebras and shape the platform through feedback.
Lead RTL design and integration for next-generation wafer-scale AI processors, driving high-performance, power-efficient chip architecture from specification and microarchitecture through silicon bring-up.
Research and develop inference algorithms and model architectures for Cerebras hardware, advancing speculative decoding, model compression, sparse attention, and other techniques to improve inference quality, latency, and throughput.
Build and operate the backend services, operational tools, and applications that help teams monitor AI cluster health, resolve incidents, and keep compute capacity available as the fleet scales.
Drive production-test strategy, silicon debug, failure analysis, and yield improvement for Cerebras wafer-scale AI processors, partnering with foundries and cross-functional teams across high-volume manufacturing.
Designs, builds, and operates secure AI agents, enterprise applications, and integrations, taking solutions from architecture and prototypes through testing, production support, and controlled business workflows.
Leads legal strategy for data center acquisitions and infrastructure development, structuring and negotiating complex transactions while advising on financing, operations, regulatory matters, and long-term partner relationships.
Lead data center and infrastructure transactions from diligence through closing, negotiate real estate and capacity agreements, and advise on construction, supply chain, regulatory, and operational matters.
Build production observability software for large-scale distributed systems, developing telemetry pipelines, internal platforms, and reliability practices that improve debugging, alerting, and system health.
Map emerging machine learning algorithms to Cerebras systems by combining performance modeling, benchmarking, and prototyping to guide implementation choices, research priorities, and future hardware–software co-design.
Build runtime components and high-performance kernels that bring novel machine learning research to efficient execution on Cerebras systems, optimizing training and inference across frameworks, compilers, runtimes, and hardware.
Own and advance detection and response capabilities by engineering reliable detections and automation, leading complex investigations, and turning attacker behavior and incident findings into lasting security improvements.
Design, build, and operate scalable NetSuite ERP solutions, integrations, and workflow automations, translating Finance and Supply Chain needs into secure, tested production systems and supporting their ongoing delivery.
Design, commission, and optimize automated manufacturing assembly and test systems, using industrial controls and robotics to improve production efficiency, product quality, equipment reliability, and safety.
Build production inference APIs and distributed serving systems that unify GPU prefill with Cerebras decode, enabling reliable model integrations, consistent user-facing behavior, and high-performance AI capabilities.
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