
501 - 1000 employees
🔧 Hardware
🤖 Artificial Intelligence
☁️ SaaS
Hardware • Artificial Intelligence • SaaS
Cerebras is a company that builds wafer-scale AI chips (the Wafer-Scale Engine) and systems purpose-built for ultra-fast AI inference and training. They offer the CS-3 system and Cerebras Inference Cloud with drop-in OpenAI API compatibility, enable on-premise, cloud, and edge deployment, and partner with companies like AMD, CrowdStrike, Flex, and major enterprises. Their product messaging emphasizes extremely large chips (58x larger than GPUs), massive speed and throughput (up to 15x faster inference, thousands of tokens per second), and use cases across model serving, fine-tuning, and pre-training. Customers include OpenAI, Meta, GSK, Mayo Clinic, AWS, and others; applications span AI infrastructure, real-time agents, genomics, drug discovery, cybersecurity, and enterprise search. Cerebras focuses on high-performance AI hardware and integrated software/platform offerings for training and inference.
🔥 2 hours ago
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501 - 1000 employees
🔧 Hardware
🤖 Artificial Intelligence
☁️ SaaS
Hardware • Artificial Intelligence • SaaS
Cerebras is a company that builds wafer-scale AI chips (the Wafer-Scale Engine) and systems purpose-built for ultra-fast AI inference and training. They offer the CS-3 system and Cerebras Inference Cloud with drop-in OpenAI API compatibility, enable on-premise, cloud, and edge deployment, and partner with companies like AMD, CrowdStrike, Flex, and major enterprises. Their product messaging emphasizes extremely large chips (58x larger than GPUs), massive speed and throughput (up to 15x faster inference, thousands of tokens per second), and use cases across model serving, fine-tuning, and pre-training. Customers include OpenAI, Meta, GSK, Mayo Clinic, AWS, and others; applications span AI infrastructure, real-time agents, genomics, drug discovery, cybersecurity, and enterprise search. Cerebras focuses on high-performance AI hardware and integrated software/platform offerings for training and inference.
• Lead deployment of AI clusters including Cerebras Wafer Scale Engine, high-speed switches, storage, and rack-level infrastructure • Coordinate rack integration of high-density compute, specialized racks, and associated power components (PDUs, busway drops) • Ensure deployment aligns with AI cluster architecture, topology, and scaling requirements • Manage installation of high-speed interconnect cabling (fiber and copper) supporting AI fabrics (east–west traffic) in Data Centers • Coordinate inter-rack and intra-rack cabling for AI clusters, including spine-leaf and pod-level designs • Ensure proper routing, airflow clearance, labeling, and testing of all AI-related cabling • Work closely with facilities teams on power capacity, cooling readiness, containment, and grounding for dense racks • Coordinate deployment sequencing with facility commissioning milestones • Validate white-space readiness before rack and cluster deployment • Troubleshoot cabling, connectivity, and integration issues impacting AI cluster bring-up • Lead root-cause analysis for deployment blockers related to cabling, hardware placement, or facilities dependencies • Support validation, burn-in, and handoff of AI clusters to operations teams • Partner with network, server, AI platform, and operations teams to align on deployment plans and readiness • Manage multiple parallel AI cluster deployments across sites or availability zones • Communicate risks, dependencies, and milestones clearly to stakeholders • Ensure deployments follow company design standards, structured cabling best practices, and AI deployment playbooks • Validate as-built documentation, labeling accuracy, and deployment checklists • Maintain accurate records for cluster configuration, cabling, and deployment status • Enforce EHS, data center safety, and access control procedures during deployment
• Bachelor’s degree in Engineering, IT, or equivalent practical experience • 10+ years of experience in data center deployments, infrastructure delivery, or integration roles • Ability to provide directions to technicians on data center floor. • Hands-on experience deploying hyperscale AI, ML, or HPC infrastructure • Strong experience with structured cabling in high-density environments, and troubleshooting • Proven ability to manage complex, cross-functional deployment programs • Familiarity with high-speed fabrics (e.g., InfiniBand, high-bandwidth Ethernet) • Experience with DCIM or deployment tracking systems • Strong attention to detail and operational rigor • Ability to perform under tight timelines and production constraints.
• 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.
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