Cerebras Systems

Develop the host and network I/O software that connects distributed AI server clusters to Cerebras’ custom hardware and RoCE network stack. You’ll optimize bandwidth, latency, CPU and memory use while debugging network behavior across software and hardware teams.

Lead the quality, reliability, and validation strategy for a new GPU inference development team. Build automated release qualification, performance benchmarking, numerical correctness, and fault-injection systems for distributed GPU inference infrastructure.

Build and operate the distributed software platform that turns Cerebras wafer-scale systems, servers, and switches into a reliable, observable AI cloud. You’ll develop Go and Python infrastructure across Kubernetes, bare-metal fleets, workload scheduling, control planes, and automated recovery.

Build the core Python infrastructure that orchestrates distributed engineering workflows across machines, clusters, and hardware systems. You’ll design scheduling, execution, testing, and developer-tooling frameworks used across Cerebras.

Build and operate the platform layer powering Cerebras’s engineering infrastructure, including Kubernetes platforms, deployment automation, CI/CD systems, and developer environments. This engineering-focused infrastructure role turns operational challenges into reliable, scalable software and platform improvements.

Lead the creation and operation of Release Integration Testing for Cerebras’s AI Inference Core, ensuring integrated features are validated and ready for reliable production releases. This hands-on technical leadership role combines test architecture, automation, cross-stack debugging, release qualification, and engineering mentorship.

Build and operate the internal platform that powers Cerebras’s security detection and response program. You’ll develop telemetry pipelines, reliable detection execution systems, and automation that accelerates investigation and response.

Staff AI Engineer responsible for architecting and building secure, governed AI agents and enterprise applications for Finance, operations, and business systems. The role combines hands-on engineering, solution architecture, platform strategy, and compliance-by-design.