Cerebras-GPT ↗
Official project, model family or research program. Follow the source for versions, releases and terms.

◎ Sunnyvale, United States
Cerebras develops Cerebras-GPT models.
Official project, model family or research program. Follow the source for versions, releases and terms.
Nolan Dey, Gurpreet Gosal, Zhiming, Chen, Hemant Khachane
Roles are tied to the linked sources. Paper authors are credited as contributors, which does not establish current employment.
Films are credited to their original channels. Selected presentations may include independent interviews and technical explanations.
The Accounting Manager role manages general ledger operations and financial reporting in compliance with U.S. GAAP. The position requires a bachelor's degree in accounting or finance and at least five years of progressive accounting experience.
The AI and Automation Engineer designs, builds, and operates secure AI solutions and enterprise automations for Finance, Accounting, and Supply Chain processes. The role requires 8+ years of experience in software engineering, Python, TypeScript, and production AI systems, with a focus on Scrum delivery and SOX compliance.
The role involves translating cluster architectures into deployment-ready infrastructure designs, including rack layouts, bills of materials, and cable mappings. Candidates must have experience in data center design and automation using languages like Python or Bash.
The role involves owning model quality and performance for Cerebras' inference offerings by designing AI-driven evaluation suites and automating release qualification. Candidates must have experience building AI agents and a strong math/stats background to create scalable measurement systems.
The role involves building and operating software to manage large AI clusters, focusing on fleet health, capacity, and incident response. Candidates must have 12+ years of experience in distributed systems and strong Go skills.
The role involves designing and building Python frameworks for Cerebras's core engineering infrastructure, including orchestration, scheduling, and distributed execution systems. Candidates must have strong software engineering fundamentals, proficiency in Python, and experience with concurrency and distributed systems concepts.
The role is a Senior SDET in Release Integration Testing for AI Inference Core, focusing on developing test automation and validating complex AI inference systems. Candidates must have strong software engineering fundamentals, proficiency in Python or Go, and experience with automated testing frameworks and CI/CD pipelines.
The role involves building and operating CI/CD systems, Kubernetes platforms, and deployment automation for Cerebras engineering infrastructure. Candidates must have 5+ years of experience in platform or DevOps engineering with strong systems fundamentals and Python proficiency.
The role involves integrating and validating high-complexity software components across AI frameworks, compilers, and hardware for Cerebras's inference stack. Candidates must demonstrate strong software engineering fundamentals and experience with complex systems, distributed software, or hardware co-design.
This role leads Release Integration Testing for AI Inference Core, defining quality strategy and managing release readiness across the software stack. Candidates must have strong software engineering fundamentals, technical leadership in test infrastructure, and experience with distributed systems or AI software.
The Application Security Engineer role focuses on owning and evolving Cerebras's vulnerability management program across applications, infrastructure, and AI platforms. Candidates must have strong application security fundamentals, hands-on vulnerability management experience, and the ability to automate security workflows using languages like Python or Go.
The Applied AI/ML Scientist role involves developing and customizing large language models to solve customer problems using Cerebras hardware. Candidates must have experience in large model training, post-training, and data curation, along with strong communication skills.
The role involves applying machine learning techniques to build scalable, high-performance systems for LLM training and deployment. Candidates must have strong Python skills, experience with PyTorch, and a solid understanding of ML fundamentals and transformers.
The role involves designing and operating secure cloud infrastructure and identity platforms in AWS and data centers. Candidates must have 5+ years of experience in cloud infrastructure, IAM, or security engineering, with strong skills in Python, Go, and Terraform.
The role involves designing and operating AWS infrastructure for Cerebras' products, focusing on reliability and scalability. Candidates must have 8+ years of experience in cloud infrastructure, SRE, or DevOps, with deep AWS and Terraform expertise.
The Cloud Quality Engineer owns end-to-end quality for weekly cloud releases and builds scalable test infrastructure for Cerebras Inference Cloud. The role requires 5+ years of experience in quality engineering, deep cloud platform knowledge, and strong systems debugging skills.
The Cluster Datacenter Manager leads compute infrastructure operations and operational reliability across multiple data center sites. The role requires 10+ years of experience in data center operations, including 5+ years leading technical teams, with strong technical judgment in server systems, networking, and secure asset handling.
The role involves managing and operating large-scale AI compute clusters to ensure infrastructure health and performance. Candidates must have 6-8 years of experience with Linux, Docker, Kubernetes, and distributed systems.
This role involves working at the interface of software and hardware for Cerebras' CoDesign and NextGen organization, focusing on kernel design, ASIC performance modeling, and system bringup. Candidates must have a degree in Computer Engineering, Electrical Engineering, or Computer Science, along with strong computer architecture knowledge and experience with C++ and Python.
This role involves characterizing and optimizing the performance of AI models on Cerebras hardware to improve computational efficiency. Candidates must have a strong background in computer architecture and at least three years of experience in relevant domains such as CPU/GPU performance or kernel optimization.
The Compute Server Platform Architect owns the server-side architecture for Cerebras CS3-based AI clusters to ensure predictable performance, scalability, and reliability. The role requires translating workload behavior into hardware requirements and leading vendor evaluations for CPU, memory, and networking components.
The Deployment Network Manager leads end-to-end execution of AI cluster deployments in large-scale data centers, managing rack integration and high-density cabling. The role requires 10+ years of experience in data center infrastructure and the ability to direct technicians on-site.
The Design Verification Engineer role involves developing verification strategies, testbenches, and coverage plans for Cerebras's AI chip architecture. Candidates must have 3-5+ years of Design Verification experience and strong skills in SystemVerilog, UVM, and debugging.
The role involves developing and maintaining infrastructure for the Cerebras software stack, focusing on automating processes in cloud and datacenter environments. Candidates must be enrolled in a university program and proficient in Python, shell scripting, and CI/CD platforms.
The role involves producing original research and technical writing on AI hardware and software, including building demos and running benchmarks. Candidates must have deep expertise in AI systems and a strong portfolio of published technical content.
The Director of Intellectual Property Counsel leads Cerebras' global IP strategy, managing patent, trademark, and trade secret assets for AI hardware and software. The role requires a J.D., USPTO registration, and 10+ years of patent prosecution experience with a technical background in AI infrastructure or related fields.
This role leads corporate FP&A for a newly public AI chip company, overseeing long-range planning, forecasting, and executive reporting. Candidates need 15+ years of experience in corporate FP&A or strategic finance, with strong financial modeling and public-company reporting skills.
This role leads the Inference Model Scaling team to enable foundation models on Cerebras hardware. Candidates must have 12+ years in compiler or ML systems and 5+ years leading engineering teams.
The role involves building and operating production distributed systems for Cerebras's cluster engineering team, focusing on Kubernetes operators and automation for bare-metal infrastructure. Candidates must have 5+ years of experience with Go, Python, and deep Kubernetes expertise, including CRDs and reconciliation semantics.
This role involves leading the Kernel Reliability team to improve the reliability of advanced compute clusters and production services. Candidates must have 6+ years of software engineering experience and 3+ years leading teams in reliability, debug, or failure analysis.
The ERP Engineer designs, builds, and operates scalable ERP solutions for Cerebras, translating complex Finance and Supply Chain requirements into reliable system capabilities. The role requires 8+ years of ERP experience and 5+ years of hands-on NetSuite expertise, including SuiteScript and API integration.
The FPGA Engineer role involves owning the in-chassis IO subsystem, including RoCE v2 network interfaces and a programmable switching fabric, for Cerebras' AI hardware. Candidates must have 5+ years of industry experience generating production FPGA solutions or a Master's/PhD with 3 years of experience, along with proficiency in Verilog and FPGA tools.
The role involves bringing up state-of-the-art models on Cerebras CSX systems within the Inference Core team. Candidates must be system-minded generalists with strong debugging skills and experience across the full AI software stack.
The role involves taking ML models from reference implementations to efficient execution on AI accelerator hardware, including model bring-up and MLIR-based lowering. Candidates must have strong C++ and Python skills, PyTorch experience, and practical MLIR knowledge.
The Hardware Research Analyst role involves producing original research and technical writing on AI hardware and software trends. Candidates must build demos, run benchmarks, and synthesize evidence to explain complex technical developments to developers and the industry.
The Head of DevRel role involves defining the developer relations vision, roadmap, and technical quality bar for Cerebras. Candidates must lead a team, build technical demos, and manage developer programs to drive platform adoption.
The Head of SOX & Internal Audit will establish and lead the company's SOX compliance program and eventually build the Internal Audit function. The role requires 10+ years of experience in Internal Audit or SOX compliance, with 5+ years in leadership, and deep knowledge of SOX, COSO, and ICFR.
The role involves maintaining, provisioning, and troubleshooting on-premise server and networking infrastructure, including physical hardware installation and Linux system configuration. Candidates must have 3-5+ years of experience in data center or infrastructure engineering with proficiency in Linux administration and network configuration.
The role involves deploying, automating, and maintaining Linux-based compute and data storage infrastructure. Candidates must have strong Linux fundamentals, Python, Ansible, shell scripting, virtualization, and storage experience.
The IT SRE Team Lead is responsible for building and running the reliability function for Cerebras' internal technology estate, including identity, endpoint management, and SaaS. The role requires a software engineering mindset to treat infrastructure as code with measurable SLOs and automated remediation.
The Kernel Engineer role involves developing and optimizing high-performance software for Cerebras's custom AI hardware. Candidates must be skilled in C++ and Python, with a strong understanding of hardware architecture and debugging.
The role involves developing and optimizing high-performance machine learning and linear algebra kernels for the Cerebras Wafer-Scale Engine. Candidates must have strong C++ programming skills, an understanding of computer architecture, and experience with parallel programming or low-level software development.
The role involves leading RTL design and integration for Cerebras's Wafer Scale Engine, managing external ASIC vendors, and collaborating with verification and physical design teams. Candidates require a Master's degree, 8-15 years of experience in high-performance RTL design, and expertise in networking and high-speed IO.
The role is a Lead Systems Signal Integrity/Power Integrity Engineer responsible for solving complex SI/PI challenges in next-generation AI compute systems. The position requires a Master's degree in Electrical Engineering and 15+ years of expertise in high-speed hardware systems.
The role involves developing and optimizing high-performance software for Cerebras's custom AI chip architecture. Candidates must have strong C++ and Python skills, experience with low-level systems programming, and a proven track record leading technical teams.
The Managing Counsel, Data Center & Infrastructure role leads legal strategy for data center acquisitions and digital infrastructure transactions. Candidates must have 10+ years of legal experience in data center or hyperscaler real estate and physical infrastructure transactions.
The Manufacturing Automation Engineer designs, implements, and optimizes automated manufacturing assembly and test systems to improve production efficiency and quality. The role requires a Bachelor's degree in a related technical field and 9+ years of experience in manufacturing automation or industrial controls.
The role involves designing and maintaining robust IT and network infrastructure across manufacturing facilities. Candidates must have deep expertise in Linux systems administration, network security, and infrastructure automation.
The Core ML team seeks an engineer to map algorithms to Cerebras architecture and characterize efficiency frontiers. The role requires analytical performance modeling, empirical benchmarking, and hands-on prototyping to optimize model quality, latency, and throughput.
The role involves inventing and evaluating advanced algorithms for efficient inference on Cerebras hardware, focusing on speculative decoding, pruning, and sparse attention. Candidates must have a PhD or master's degree with significant research experience and strong Python skills.
The Core ML team seeks an engineer to bridge research ideas and efficient execution on Cerebras systems. The role involves implementing high-performance kernels and runtime components for LLM training and inference.
The role involves leading the design and implementation of system-level debugging, validation, and observability platforms for Cerebras's AI chip. Candidates must have strong proficiency in C++ and Python, with experience debugging complex hardware/software systems and building high-performance tooling.
The role involves building performance models and optimizing kernel microcode to improve ML inference speed on Cerebras hardware. Candidates require a degree in Electrical Engineering or Computer Science, strong computer architecture knowledge, and 3+ years of relevant experience.
The role involves building performance models and optimizing kernel microcode to improve ML model inference speed and throughput on the Cerebras Wafer Scale Engine. Candidates require a degree in Electrical Engineering or Computer Science, strong computer architecture knowledge, and 3+ years of experience in performance optimization or HPC.
The role involves building and securing network infrastructure for data centers, cloud environments, and AI systems. Candidates must have 7+ years of experience in network security and hands-on skills with firewalls, segmentation, and AWS networking.
The role involves building and securing network infrastructure for data centers, cloud environments, and AI systems. Candidates must have 7+ years of experience in network security and proficiency with firewalls, segmentation, and automation tools.
The Network Systems Architect defines scale-up and scale-out network architectures for Cerebras platforms, including proprietary accelerator interconnects and switching. The role requires translating workload communication patterns into measurable fabric requirements and making technical decisions grounded in low-level implementation experience.
The Physical Design Engineer role involves driving PPA strategy and owning physical design from RTL to tapeout for Cerebras's AI chip. Candidates require 7+ years of experience in physical design, verification, and tools like Calibre or ICC2.
The role is a hands-on individual-contributor position responsible for establishing and governing physical security standards across contract manufacturing locations. It requires five or more years of experience in manufacturing or industrial physical security, with a focus on intellectual property protection and cleanroom operations.
The role involves developing and optimizing automated manufacturing test solutions for advanced AI hardware, including test fixtures and production processes. Candidates require a technical degree and 5+ years of experience in manufacturing test development, hardware validation, or production engineering.
The Principal AI Security Engineer leads hands-on security engineering for enterprise IT, infrastructure, and AI platforms. The role requires 10+ years of experience in security engineering and strong hands-on ability in Python and at least one additional production language.
The Principal ML Investigator will lead a new ML team to develop research and advanced development capabilities aligned with Cerebras hardware. The role requires a PhD in Computer Science, strong ML theory, and experience engineering ML systems for scale or production deployment.
The Principal Network Security Architect leads the design and evolution of Cerebras's enterprise, data center, and cloud networks. The role requires 10+ years of experience in network engineering, deep expertise in routing and switching, and proficiency in network automation and cloud networking.
The Regional Data Center Manager leads operations, deployment execution, and infrastructure performance for Cerebras's Finland-based and broader European AI deployments. The role requires bilingual fluency in Finnish and English, 5-10+ years of practical data center experience, and strong knowledge of MEP systems to manage high-density AI clusters.
The Regional Data Center Manager leads infrastructure operations and deployment execution across Western Canada sites. The role requires 5-10+ years of data center experience, knowledge of MEP systems, and the ability to manage local teams while executing HQ-driven requirements.
The Release Qualification Team Lead owns end-to-end release qualification for Cerebras Cloud, Inference Platform, and Inference API. The role requires 7+ years of experience in software integration or quality engineering, with proven leadership in building release processes and mentoring engineers.
The SEC Reporting & Technical Accounting Manager supports SEC filings and technical accounting at Cerebras Systems. The role requires strong US GAAP skills, 5+ years of experience, and proficiency in tools like Workiva and NetSuite.
The role involves securing and scaling enterprise IT, cloud, network, and infrastructure environments for Cerebras. Candidates must demonstrate an automation-first mindset and experience in security, reliability, and operational excellence.
The role involves driving chip design, micro-architecture, and RTL development for Cerebras Wafer Scale Engine systems. Candidates must have a Master's degree and 8+ years of experience in high-performance RTL design and integration.
The role involves building and scaling backend services for Cerebras Inference Cloud, including APIs, data pipelines, and systems for billing and account management. Candidates must have strong backend engineering fundamentals, experience with distributed systems, and a track record of owning complex production systems.
The Senior Counsel, Data Center & Infrastructure role supports the Global Data Centers team with acquisitions, development projects, and infrastructure transactions. Candidates must have 6+ years of legal experience in data center or infrastructure transactions and fluency in technical infrastructure terms.
The role manages end-to-end delivery of white-space fit-out projects in colocation environments for Cerebras data centers. Candidates need 5-7 years of mission-critical construction experience and strong project controls skills.
The role involves leading the design and optimization of security detections, playbooks, and workflows to identify and respond to incidents. Candidates must have 5+ years of experience in detection engineering or incident response, with strong proficiency in Python and SQL.
The role involves leading testing strategy and execution for AI/ML models and Cerebras inference solutions. Candidates must have 5+ years of experience in software integration or quality engineering and expertise in automation using Python, C++, or Go.
The Senior Manager - Cluster Security role leads security engineering for Cerebras's large-scale AI clusters, ensuring end-to-end security and privacy across hardware, networking, and software. Candidates must have 3+ years of engineering leadership in distributed systems security and strong experience with multi-tenancy and cluster networks.
The Senior Manager, Production & Fleet Operations role leads day-to-day operational management of Cerebras-managed production infrastructure. The position requires 8+ years of infrastructure operations experience and 3+ years leading technical operations teams to establish scalable fleet health and restoration processes.
The Senior Manager, Service Operations & Enablement role owns operational readiness and on-premises O&M models for Cerebras infrastructure deployments. The position requires 8+ years in infrastructure operations and 3+ years leading teams to establish training, certification, and operational knowledge management frameworks.
The Senior Operations Accountant supports monthly close and financial reporting for inventory, manufacturing costs, and global leases. The role requires a bachelor's degree, four or more years of accounting experience, and strong knowledge of U.S. GAAP, ASC 330, and ASC 842.
The Senior Product Manager for AI Models leads the strategic model portfolio, deciding which frontier and open-source models ship and how they perform. The role requires 5+ years of product management experience, 5+ years of technical work experience, and expertise in the open-source model ecosystem including PyTorch and Hugging Face.
The role involves driving test strategy for Cerebras Wafer Scale Engine in Taiwan, focusing on ATE test development and yield enhancement. Candidates require 10+ years of semiconductor testing experience and expertise with the Advantest V93000 platform.
The Senior Runtime Engineer designs and develops high-performance distributed software to orchestrate massive compute and data pipelines for AI training and inference. The role requires 3+ years of experience in high-performance or distributed systems, with strong C/C++ programming skills and expertise in multi-threading and performance optimization.
The role involves owning quality and reliability for the Cerebras Inference Platform, including CI/CD pipelines and Kubernetes deployments. Candidates must have 3+ years of experience in software or infrastructure engineering with strong Python or Go skills.
The role involves designing and automating tests for large-scale AI cluster infrastructure to ensure high reliability. Candidates must have strong coding skills and experience with distributed systems, hardware, and software testing.
The role involves designing and automating tests for large-scale AI cluster infrastructure, focusing on reliability, security, and performance. Candidates must have 10+ years of experience in distributed systems testing and strong coding skills in Python, Golang, or C/C++.
The role is a Senior Software Engineer position on the Inference Cloud team, responsible for building and operating cloud services and Kubernetes infrastructure. Candidates must have 5+ years of experience, strong Kubernetes expertise, and proficiency in Go or another backend language.
The role involves building and evolving the ML API layer for Cerebras's disaggregated AI inference systems, ensuring reliable access across heterogeneous backends. Candidates must have 5+ years of software engineering experience, strong Python skills, and proficiency in production service languages like Go, C++, or Rust.
The Senior Staff AI Accelerator Performance Architect role involves guiding the evolution of next-generation AI systems by connecting real workloads to architectural behavior and identifying bottlenecks. Candidates must possess deep knowledge of hardware architecture and 7+ years of experience in performance analysis or modeling for high-performance computing systems.
The role involves developing verification strategies, testbenches, and coverage plans for Cerebras's AI chip architecture. Candidates must have 15+ years of Design Verification experience and strong skills in SystemVerilog, UVM, and debugging.
The role involves building security controls for on-prem and cloud clusters, driving hardening across bare metal, virtualized, and k8s levels. Candidates need 8-10 years of experience in heterogeneous compute, kubernetes hardening, and networked system security.
The role involves managing and supporting NetSuite and adjacent enterprise platforms for Finance and Supply Chain operations. Candidates require 6+ years of ERP experience and 4+ years of NetSuite administration.
The role involves developing software for the Host and Network IO path in Cerebras' AI chip architecture, focusing on optimizing bandwidth and latency. Candidates must have strong skills in socket programming and RDMA Verbs, along with experience in large software environments and hardware interaction.
This role involves collaborating with engineers to design and implement low-level software for AI infrastructure, focusing on performance and reliability. Candidates must be recent graduates with proficiency in C/C++ and an interest in systems programming or hardware interaction.
The role involves developing and maintaining CI/CD pipelines, managing artifact lifecycle systems, and provisioning cloud infrastructure to support build workloads. Candidates require 4-8 years of experience in DevOps or software engineering, with proficiency in CI/CD, cloud platforms, and containerization.
The role involves building automation for large-scale AI cluster deployments, including provisioning, configuration, and validation. Candidates need 2+ years of data center deployment experience and strong Python and Bash skills.
The role involves productionizing and optimizing a GPU inference stack for Cerebras's disaggregated AI systems, focusing on reliability and performance. Candidates must have 5+ years of experience in C++ and Python, with expertise in production inference systems and GPU performance optimization.
The role involves designing and maintaining production software for Cerebras's Inference Platform, focusing on orchestration, Kubernetes, and high-performance systems. Candidates must have 3+ years of experience in distributed systems and proficiency in Go or C++.
The role involves improving the reliability of Cerebras's advanced compute clusters and inference services by working close to the code. Candidates must have strong programming skills in C/C++ and Python, along with solid foundations in operating systems and systems programming.
The role involves assessing and hardening the source-to-artifact pipeline, including SLSA processes and CI/CD artifacts. Candidates need 8-10 years of experience in software supply chain security, SDLC topics, and hands-on DevOps engineering.
The Sr. Datacenter Provisioning Engineer provisions and validates network infrastructure and servers across large-scale data center deployments. The role requires at least five years of experience in network provisioning, SRE, or related fields, along with proficiency in Python, Linux, and cloud platforms.
The role involves designing and developing software for system resiliency and high availability in distributed AI inference environments. Candidates must have a Master's degree and 18 months of experience in software engineering or related roles, with expertise in cloud infrastructure and containerization.
The role involves leading and contributing to projects on the Inference Platform team, which owns the orchestration layer for datacenter clusters. Candidates must have 8+ years of experience in software engineering and deep expertise in distributed systems architecture, ideally with Kubernetes.
The role involves post-silicon validation, testing, and debugging of Cerebras Wafer Scale Engines. Candidates must have a Master's degree and three years of experience in hardware or related engineering.
The Staff Business Systems Analyst role connects business strategy, process design, and enterprise systems across BIS-supported functions. Candidates must have senior experience in business analysis, ERP platforms, and public-company compliance to lead process mapping and requirements definition.
The role involves designing and implementing secure, scalable cloud infrastructure and identity platforms in AWS and data centers. Candidates must have 7+ years of experience in cloud infrastructure, IAM, or security engineering, with strong skills in Python, Go, and Terraform.
The role involves developing verification strategies, testbenches, and coverage plans for Cerebras's AI chip architecture. Candidates must have 10+ years of Design Verification experience and strong skills in SystemVerilog, UVM, and debugging.
The role is a Staff GPU Inference SDET responsible for leading quality and validation for a new GPU Inference Development team. Candidates must have 8+ years of experience in SDET or systems testing, with expertise in GPU cluster infrastructure and LLM serving engines.
The role involves developing and optimizing high-performance software for Cerebras's custom AI chip architecture. Candidates must design machine learning kernels in C++ and Python, leveraging parallel programming and low-level assembly for HPC workloads.
The role involves designing and maintaining CI/CD pipelines, artifact lifecycle systems, and cloud infrastructure for build and test workflows. Candidates must have 7+ years of experience in software engineering or DevOps, with strong skills in infrastructure automation and troubleshooting.
The role involves productionizing and optimizing a GPU inference stack for Cerebras's disaggregated AI systems, focusing on reliability and performance. Candidates must have 8+ years of experience, strong C++ and Python skills, and expertise in high-performance model-serving frameworks and GPU execution.
The role involves building and maintaining production ML inference APIs for a disaggregated AI system that combines GPU prefill with Cerebras decode. Candidates must have 5+ years of software engineering experience and strong skills in Python, Go, and systems languages like C++ or Rust.
The role involves owning the long-term architecture and roadmap for Cerebras's observability platform, including metrics, logs, traces, and events. Candidates must have 8+ years of software engineering experience and 4+ years building observability platforms at significant scale.
This role involves owning the end-to-end program schedule for hardware and software integration of Cerebras' wafer-scale supercomputers. Candidates must have 8+ years of technical program management experience with a focus on hardware design and cross-functional engineering collaboration.
The Supplier Quality Engineer role supports supplier quality for components and system-level products used in Cerebras systems. Candidates must be a 2026 new graduate with a bachelor's degree in a related technical field and foundational knowledge of quality engineering and manufacturing.
The Systems Debug Engineer role involves diagnosing complex multi-domain hardware failures at the system, board, and component levels. Candidates must have 3-5+ years of experience in hardware bring-up or failure analysis and strong analytical skills.
The role supports the Head of Data Center Acquisition by sourcing and managing a pipeline of data center capacity opportunities. Candidates must have 1-4 years of experience in acquisitions or sourcing, with strong outreach and analytical skills.
This role provides technical leadership for server and network platform programs, including new product introductions, across Cerebras AI clusters. Candidates must have 8+ years of experience in technical leadership or systems engineering for infrastructure platforms and strong knowledge of server architecture and networking.
Current official-feed vacancies. Follow each job for its complete description and application terms.
Profile reviewed 2026-10-30. City-level approximate marker; not a lab street address.