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高级系统软件工程师 - NV 云函数

Senior Systems Software Engineer - NV Cloud Functions

开发工程限定地区(需当地身份)
公司NVIDIA
薪资未公开
工作地点India
地域资格限定地区(需当地身份)
时区要求日间重叠约 6 小时,基本正常作息
用工类型Full Time
发布时间今天
数据来源Himalayas
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注意地域限制:该职位明确限定在 India 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

今天,我们正在利用人工智能的无限潜力,定义计算的新时代。在这个时代,我们的GPU将成为计算机、机器人和自动驾驶汽车的大脑,能够理解世界。完成前所未有的事情需要远见、创新和全球顶尖人才。作为NVIDIA的一员,你将置身于一个多元、支持性的环境中,每个人都能受到激励,发挥最佳水平。加入我们的团队,看看你如何对世界产生持久的影响。NVIDIA Cloud Functions(NVCF)是一个开源平台,将工作负载与GPU连接起来。它让团队能够在世界各地的区域和集群中部署、管理和提供GPU加速的容器化应用。该平台在去中心化的GPU集群之间路由推理、流媒体和批处理任务。这使得端点可以可重复地扩展,无论是在本地还是在云端。

我们正在寻找一名高级系统软件工程师加入我们的团队。你将专注于提升一个将AI工作负载路由到分布式GPU舰队的系统的性能、可靠性和扩展性。你将在一个现在完全开源的多语言平台上工作,包括控制平面和边缘部署。这项工作适合在系统性能、分布式系统和基于Kubernetes的运行时方面有深厚经验的人。我们寻找希望学习和成长的工程师。在优先级快速变化的环境中,你将面临挑战,洞察力、专注力和执行力是关键。

你将从事的工作:

  • 你将在一个分布式团队中工作,探索创新的方法,使基于GPU和DPU加速的应用程序在最新的NVIDIA硬件上更容易开发、部署和监控。
  • 使用Java、Go和Rust设计并发布服务,在公共仓库中公开开发,你的提交、设计提案和评审对社区都是透明的。
  • 优化云原生的构建、测试、集成和发布流程。
  • 与NVIDIA内部的工程团队合作,使该平台与相邻的NVIDIA技术集成,包括KAI调度器、NVIDIA NIM、Grove和Dynamo。
  • 协助维护一个开源项目。你将处理社区的问题和拉取请求,并编写开发者可以在此基础上构建的文档。

我们需要看到:

  • 计算机科学或相关领域的学士或硕士学位
  • 3年以上实际软件工程经验
  • 对系统编程的精通
查看英文原文

Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA Cloud Functions (NVCF) is an open-source platform that links workloads to GPUs. It lets teams deploy, manage, and serve GPU-accelerated, containerized applications across regions and clusters worldwide. The platform routes inference, streaming, and batch jobs across decentralized GPU clusters. This allows endpoints to scale repeatably, whether hosted on-prem or in the cloud.
We are seeking a Senior Systems Software Engineer to join our team. You will focus on improving the performance, reliability, and scaling behavior of a system that routes AI workloads onto distributed GPU fleets. You will work on a polyglot platform that is now fully open source, with both control plane and edge deployments. The work suits someone with deep experience in systems performance, distributed systems, and Kubernetes-based runtimes. We are looking for engineers who want to learn and grow. Expect to be challenged in an environment with rapidly shifting priorities, where insight, focus, and execution are key.
What you will be doing:

  • You'll be working in a distributed team that explores innovative ways to make GPU- and DPU-accelerated applications easier to develop, deploy, and monitor on the latest and greatest NVIDIA hardware.
  • Design and ship services in Java, Go, and Rust, building in the open on a public repository where your commits, design proposals, and reviews are transparent to the community.
  • Work on automating and optimizing build, test, integration, and release processes for cloud native.
  • Partner with engineering teams across NVIDIA so the platform integrates with adjacent NVIDIA technologies, including the KAI Scheduler, NVIDIA NIM, Grove, and Dynamo.
  • Help steward an open-source project. You will triage community issues and pull requests and write docs contributors can build on.

What we need to see:

  • Bachelor’s or Master’s Degree in Computer Science or equivalent experience
  • 3+ years of hands-on software engineering.
  • Expert-level knowledge in a systems programming language (Go, C, Rust) and a proven understanding of Data Structures, Algorithms, and Distributed Software Architecture
  • Strong understanding of container orchestration systems (Kubernetes) and container technologies with hands-on automation experience in continuous integration frameworks like GitLab & ArgoCD.
  • Expertise in a scripting language (Bash, Python) and knowledge and experience working with the system internals of Unix/Unix-like kernels such as Linux.
  • Understanding of performance, security, and reliability in complex distributed systems.

Ways to stand out from the crowd:

  • Background with pub-sub models and message queues
  • Experience optimizing for high-throughput network paths, with a working understanding of unary versus streaming and bidirectional protocols across HTTP/2 and gRPC.
  • Experience with developing Kubernetes Custom Resources and Operators deployed in Cloud Service Providers

With competitive salaries and a generous benefits package, NVIDIA is considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking individuals in the industry working for us. Due to unprecedented growth, our exclusive engineering teams are expanding rapidly. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you!
Originally posted on Himalayas

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