Posted 9 days ago
The Senior Research Engineer will adapt, design, prototype, validate, and optimize language and vision models for efficient inference on Cerebras hardware. Responsibilities include researching inference techniques such as speculative decoding, pruning and compression, and sparse attention; training and evaluating models; profiling and troubleshooting performance; and collaborating with software, hardware, and product teams to deliver projects.
Posted 9 days ago
The Senior AI Fleet Platform Software Engineer will build and operate software for managing large AI cluster fleets, including backend services, operational tools, and user-facing applications. The role focuses on fleet health visibility, incident response automation, reliable distributed systems, and collaboration with infrastructure and operations teams to lead projects through production.
Posted 18 days ago
The Staff Software Engineer, Inference API will build and evolve production machine learning inference APIs and the serving platform for heterogeneous GPU and Cerebras accelerator systems. Responsibilities include model integration, API compatibility, request routing, performance optimization, correctness validation, reliability and observability, testing infrastructure, developer tooling, and cross-functional collaboration.
Posted 20 days ago
Cerebras Systems is hiring a Staff Software Engineer to build and evolve production machine-learning inference APIs across heterogeneous GPU and Cerebras accelerator backends. The role covers model integration, API compatibility, distributed serving, performance optimization, correctness, observability, testing infrastructure, and developer experience, with close collaboration across compiler, runtime, infrastructure, product, and customer-facing teams.
Posted 20 days ago
Cerebras Systems is seeking an AI Data Center Infrastructure Engineer to translate cluster architectures into deployment-ready infrastructure designs. The role includes creating rack layouts, equipment layouts, bills of materials, power allocations, port and cable maps, adapting designs to site constraints, supporting deployments, and automating repeatable design workflows.
Posted a month ago
Cerebras Systems is seeking a DevOps Engineer Intern to develop and maintain infrastructure for building, testing, operating, simulating, and evaluating its software stack. The role focuses on automating cloud and datacenter workflows, maintaining CI/CD pipelines, creating Python and shell tools, and managing Docker and Kubernetes environments.
Posted 2 months ago
The Data Center Provisioning Engineer provisions, commissions, validates, and troubleshoots network infrastructure, servers, and related systems across large-scale data center deployments. The role develops scalable automation and provisioning processes, coordinates with engineering, vendor, and operations teams, and supports infrastructure handoff and production readiness across multiple sites.
Posted 2 months ago
The Cluster Operations Software Engineer will manage, operate, and optimize advanced AI compute clusters, ensuring infrastructure health, performance, availability, and capacity. The role includes building operational platforms, APIs, automation, monitoring, dashboards, and reliability tooling, as well as troubleshooting distributed systems and participating in 24/7 on-call support.
Posted 2 months ago
Cerebras Systems is hiring a Staff Software Engineer to productionize and optimize GPU-accelerated inference systems across custom APIs, vLLM, PyTorch, ROCm, and AMD GPU infrastructure. The role owns operational readiness, reliability, performance optimization, numerical correctness, benchmarking, and debugging across application, runtime, distributed-system, and hardware layers.
Posted 2 months ago
Cerebras Systems is seeking a hands-on SDET Technical Lead to establish and lead Release Integration Testing for its AI Inference Core. The role owns release integration strategy, inference-path readiness, cross-stack validation, branch stability, rollout triage, test architecture, automation, debugging, quality metrics, and technical mentorship across software, infrastructure, and hardware teams.
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