Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Skills: 3D Solids Modeling, Solidworks, PLM Systems, GD&T, Tolerance Analysis
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Skills: Enterprise IT Security, Cloud Security, Network Security, Systems Administration, Automation
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Skills: Software Architecture, Full Stack Development, Distributed Systems, Python, C++
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Skills: AI Agents, Model Evaluation, Docker, Git, CI/CD
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Skills: C++, C, Systems Programming, Networking, Embedded Systems
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Skills: Electrical Signal Integrity Analysis, Hardware Bring-up & Debug, Functional and Electrical Characterization, Test Automation, High Speed Interfaces & Protocols
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Skills: Physical Design, Synthesis, Place and Route, Timing Closure, Physical Verification
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Skills: Linux Administration, Network Engineering, Palo Alto Firewalls, Ansible, BGP
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Skills: SMT Manufacturing, IPC Standards, Statistical Process Control, PFMEA, 8D Problem Solving
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Skills: Business Operations, Operational Analytics, KPI Architecture, Process Redesign, Executive Communication
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Manager - Data Center Asset tracking and Accounting
Binangonan, Rizal, Philippines · On-site
Senior$3.7B raised
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale …
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Full-time
postgraduate degree
Posted 70d ago
~40 hrs/week
Responsibilities
Design and architect front-end network fabrics for AI/ML and HPC clusters to optimize throughput and latency. Lead network reliability efforts, including building automation tools and implementing SRE-grade observability pipelines.
Requirements
Requires a PhD with 5+ years or a Master's with 10+ years of experience in large-scale datacenter networking. Must possess deep expertise in networking protocols, Python programming, and distributed systems debugging.
Full job description
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About The Role
We are looking for a Network Architect to join our Cluster Engineering Team and help shape the front-end datacenter and interconnect fabric for the current and next generations of our AI clusters. You will partner closely with hardware vendors, internal networking teams, and industry peers to define best-in-class network architectures that deliver resilient, reliable, and high-throughput connectivity for large-scale AI workloads.
This is a deeply technical role that spans the full stack, from host-side networking and NIC behavior up through cluster-level coordination and requires fluency across diverse hardware components (including network switches, NICs, and the Accelerator Compute Engine) and the software layers that drive them. You will own proof-of-concept work for new network designs and features, and you will be the central technical voice for network reliability across the organization.
What You'll Do
Design and architect front-end network fabrics for AI/ML and HPC clusters, optimizing for high resource utilization, low latency, and high-throughput communication.
Build proof-of-concept implementations of new network designs and features, and drive them from prototype through production rollout.
Identify and resolve performance and efficiency bottlenecks across the host-NIC-fabric
Automate the deployment, configuration, and validation of network infrastructure using Python, including topology provisioning, fabric bring-up, config generation, and regression Strong programming skills are essential; this role builds tools, not just runbooks.
Stand up and operate SRE-grade telemetry and observability for the cluster network: streaming telemetry (gNMI, OpenConfig, sFlow/IPFIX), metrics pipelines, alerting, and incident workflows. Define the SLIs/SLOs that govern network reliability and drive blameless post-incident analysis.
Lead network debugging in large distributed-systems environments spanning multiple platforms and protocols, including deep dives into RoCEv2, PFC/DCQCN, ECMP hashing, congestion behavior, and packet-level forensics.
Lead cross-functional, multi-phase technical projects spanning hardware, firmware, host networking, and cluster software.
Collaborate with vendors and industry partners to shape network hardware and feature roadmaps.
Represent the company in industry forums, standards bodies, and technical communities.
Serve as the central point of contact for network reliability issues across the cluster.
Skills & Qualifications
Ph.D. in Computer Science or Electrical Engineering with 5+ years of industry experience, or Master's in CS/EE with 10+ years of industry experience.
Solid experience in designing large-scale networks in datacenter and cloud environments.
Extensive hands-on experience debugging networking issues in large distributed systems with multiple platforms and protocols.
Demonstrated track record leading multi-phase, multi-team technical projects to completion.
Technical Skills
Deep expertise across networking platforms: Juniper, Arista, Cisco, and open-box / disaggregated NOS architectures (SONiC).
Strong working knowledge of networking protocols and fabric technologies: VXLAN, EVPN, RoCEv2, BGP, DCQCN, PFC, ECN, and streaming telemetry.
Programming and automation: proficiency in Python (and/or Go) for building network automation, validation, and tooling. Comfort with config generation frameworks (Ansible, Jinja2), gNMI, and CI/CD pipelines for network infrastructure.
SRE and observability: hands-on experience with streaming telemetry pipelines, time-series databases (Prometheus, InfluxDB), visualization (Grafana), log aggregation, and modern incident-management Ability to define SLIs/SLOs and instrument the network for proactive reliability.
Familiarity with network visibility, management, and packet-capture/analysis tools.
Strongly Preferred
Prior experience at hyperscalers or cloud service providers.
Experience with AI/ML or HPC cluster networking, including lossless Ethernet design, rail-optimized topologies, and collective-communication traffic patterns.
Track record of contributions to open-source networking projects, standards bodies, or industry conferences.
Why Join Us
You'll work on networks that move data at a scale and density few teams ever touch, with direct impact on training and inference performance for some of the largest AI systems in the world. You'll have the autonomy to shape architecture decisions, the resources to prototype real hardware, and a peer group that takes both engineering rigor and operational reliability seriously.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
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.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
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Related keywords
AI ChipHPCNetwork FabricJuniperAristaCiscoSONiCVXLANEVPNRoCEv2BGPDCQCNPFCECNPythonGo
Cerebras Systems is the world's fastest AI inference. We are powering the future of generative AI. We’re a team of pioneering computer architects, deep learning researchers, and engineers building a new class of AI supercomputers from the ground up.
Our flagship system, Cerebras CS-3, is powered by the Wafer Scale Engine 3—the world’s largest and fastest AI processor. CS-3s are effortlessly clustered to create the largest AI supercomputers on Earth, while abstracting away the complexity of traditional distributed computing.
From sub-second inference speeds to breakthrough training performance, Cerebras makes it easier to build and deploy state-of-the-art AI—from proprietary enterprise models to open-source projects downloaded millions of times.
Here’s what makes our platform different:
🔦 Sub-second reasoning – Instant intelligence and real-time responsiveness, even at massive scale
⚡ Blazing-fast inference – Up to 100x performance gains over traditional AI infrastructure
🧠 Agentic AI in action – Models that can plan, act, and adapt autonomously
🌍 Scalable infrastructure – Built to move from prototype to global deployment without friction
Cerebras solutions are available in the Cerebras Cloud or on-prem, serving leading enterprises, research labs, and government agencies worldwide.
👉 Learn more: www.cerebras.ai
Join us: https://cerebras.net/careers/
Offices: 1237 E Arques Ave, Sunnyvale, California 94085, US · 150 King St W, Toronto, Ontario M5H 1J9, CA · Tokyo, JP · Bangalore, IN
artificial intelligencedeep learningnatural language processinginferencemachine learningllmAIenterprise AIand fast inferenceSemiconductor
Cerebras Systems is the world's fastest AI inference. We are powering the future of generative AI. We’re a team of pioneering computer architects, deep learning researchers, and engineers building a new class of AI supercomputers from the ground up.
Our flagship system, Cerebras CS-3, is powered by the Wafer Scale Engine 3—the world’s largest and fastest AI processor. CS-3s are effortlessly clustered to create the largest AI supercomputers on Earth, while abstracting away the complexity of traditional distributed computing.
From sub-second inference speeds to breakthrough training performance, Cerebras makes it easier to build and deploy state-of-the-art AI—from proprietary enterprise models to open-source projects downloaded millions of times.
Here’s what makes our platform different:
🔦 Sub-second reasoning – Instant intelligence and real-time responsiveness, even at massive scale
⚡ Blazing-fast inference – Up to 100x performance gains over traditional AI infrastructure
🧠 Agentic AI in action – Models that can plan, act, and adapt autonomously
🌍 Scalable infrastructure – Built to move from prototype to global deployment without friction
Cerebras solutions are available in the Cerebras Cloud or on-prem, serving leading enterprises, research labs, and government agencies worldwide.
👉 Learn more: www.cerebras.ai
Join us: https://cerebras.net/careers/
Offices: 1237 E Arques Ave, Sunnyvale, California 94085, US · 150 King St W, Toronto, Ontario M5H 1J9, CA · Tokyo, JP · Bangalore, IN
artificial intelligencedeep learningnatural language processinginferencemachine learningllmAIenterprise AIand fast inferenceSemiconductor