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我们是专注于大模型服务平台的技术团队，我们的核心业务是提供高效稳定的大模型推理服务API，帮助各行各业轻松利用大模型的强大能力，正在寻找一位有实力的Site Reliability Engineer (SRE) 加入我们，共同打造更可到的大模型服务平台。 负责AI基础设施算力资源的规划、运营管理与精细化数据体系建设。通过系统化、数据化方法提升GPU资源利用率、周转率与成本效益，保障AI训练/推理任务的高效稳定运行，支撑业务快速发展。…
Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge…
Clockwork Systems, founded by Stanford researchers, builds software-driven fabrics that boost GPU cluster utilization. This on-site Palo Alto role designs and implements low-level systems software for fault-tolerant, high-performance distributed GPU training, working deep in the internals of PyTorch, NCCL, and CUDA with strong C/C++ and distributed-systems skills.
Senior engineer on Radiant's Platform team who architects, builds, and operates an AI-native cloud platform — virtualisation, bare-metal provisioning, Kubernetes, high-performance networking/storage, security hardening, and observability — so teams can run HPC and AI/ML workloads reliably at scale. Core stack: Kubernetes, Terraform, Ansible, Go, Python, Linux.
Senior architect at Credo's San Jose office designing system-level memory and interconnect architecture that links XPUs (NPU/GPU/custom silicon) across node, rack, and cluster scale so large LLM training and inference run efficiently. Requires computer-architecture depth; hands-on NPU silicon production experience strongly preferred. Base pay $160k-$220k plus bonus and equity.
Owns the product experience and lifecycle for bringing new AI infrastructure clusters onto Radiant's platform — onboarding, validation, benchmarking, provisioning and automation — partnering with infrastructure, SRE, networking, storage and hardware teams. A highly technical role spanning GPUs, Kubernetes/Slurm, RDMA fabrics, distributed storage and observability.
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading…
A pre-sales solutions architect on a three-person land-and-expand team covering Northern EMEA (Nordics/Benelux), leading technical discovery, solution design, and proof-of-concepts for AI labs and enterprises running demanding GPU workloads. Work spans ML training workflows and MLOps tooling down to Kubernetes, GPU infrastructure, and high-performance networking.
关于我们 我们自建 GPU 集群，对上提供 AI 推理裸金属服务。团队成员来自【头部云厂商、互联网大厂、硬件厂商等】，在大规模集群和高性能系统方面有深厚积累。 网络性能直接影响推理服务的时延、吞吐和稳定性。我们希望你在网卡与主机网络层面持续优化，全面提升集群的通信性能和可靠性。 岗位职责 1. 网卡与通信性能优化：深入网卡、PCIe、驱动和内核等层面，分析并优化单机内和多机间的 RDMA…
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at…
A hands-on senior escalation engineer (L4) on DDN's Infinia Core team in Pune, owning critical customer issues in enterprise/hyperscale storage environments — leading root-cause analysis, war rooms, runbooks and product feedback loops. Requires deep Linux, file systems (S3/POSIX/NFS), Python/Go/C++, and RDMA/NVMe-oF expertise.
负责灵骏机头机尾网卡与软件栈的规划和技术演进，面向大规模 AI 集群，围绕 Scale-Out 网络推动网络架构设计、技术选型与方案落地。负责自研与商用网卡路线评估、RDMA 特性演进、容器网络方案，并持续评估新一代芯片互联与 AI 网络技术对灵骏架构的影响。 核心职责 1. 负责机头机尾网卡的选型与技术演进，包括自研网卡和商用网卡路线 2. 推动灵骏 Scale-Out 网络架构的规划与演进 3. 推动 RDMA…
1、负责大规模 GPU/异构计算集群稳定性架构和运维体系设计，对集群可用性、交付效率、资源利用率和运维成本负责。 2、主导 AI 基础设施运维平台的架构设计与建设，形成覆盖交付、监控、诊断、变更、容量、容灾和故障自愈的工程体系。 3、建立面向 AI 训练与推理场景的 SLI、SLO、SLA 及稳定性度量体系，推动重大故障治理和系统性风险消除。 4、主导集群交付标准、运维规范和质量准入机制建设，推动跨地域、跨团队场景下的标准化复制。…
We are seeking an experienced engineer to join our team that owns the network stack for EC2 distributed AI/ML systems. The team develops support for a variety of frameworks and communication libraries including NCCL,…
5C DATA CENTERS Join the Future of Digital Infrastructure Are you a passionate Senior Cloud System Administrator looking to make a meaningful impact? We're building the next generation of digital infrastructure…
Leads architecture and performance for CoreWeave’s Kubernetes-native AI inference platform, optimizing GPU resource management and cost-per-token under strict SLAs.
Designs and sells AI infrastructure solutions for high-performance GPU workloads, working with AI labs and enterprises across Northern EMEA while bridging ML training needs with bare-metal infrastructure and MLOps tooling.
Senior engineer builds and optimizes CoreWeave’s Kubernetes-native AI inference platform, improving latency, throughput, and reliability to meet strict P99 SLAs while mentoring peers.
Senior engineer building and optimizing CoreWeave's Kubernetes-native AI inference platform to meet strict latency and reliability SLAs, using Python/Go, CUDA, and distributed systems.
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