Senior Systems Software Engineer - Accelerated Spark Applications
现在，我们正在利用人工智能来定义下一个计算机时代的无限潜力。我们的 GPU 作为能够理解世界的大脑，机器人和自动驾驶汽车的时代。做以前从未完成过的事情需要视觉，创新和世界上最好的才华。作为 NVIDIAN,你将沉浸在多元化的支持环境中，每个人都会受到启发去做自己的最佳工作。加入团队看看你如何对世界产生持久影响。公司正在寻找 APPHACE SPARK 加速集团的高级系统软件工程师.GPU 加快数据处理已经从概念证明转向生产部署。企业现在认识到需要加快计算来应对大型数据处理需求。多节点 GPU 部署降低云计算成本，降低批量 ETL 工作负载的延迟。在 NVIDIA,我们通过一个开源插件加速了 APPHAKE 应用程序在 GPU 上而不需代码变化，我们的 cuDF Spark 库与 AWS EMR,Databricks,Google Dataproc,Oracle Cloud Data Flow,Bytedance Volcengine,Tencent 和 Cloudera 相结合。这一角色是 NVIDIA 内部作为一个处理的 Spark 服务运行该加速器的团队。该服务在客户 SLA 下，每小时在 Kubernetes 和 AWS 上完成了 NVIDIA 内部数据平台的生产数据管道。它将 cuDF Spark 插件和 CPU/GPU 工作负载路由器包装到基于 Spark Connect,Kyuubi,Helm 和 Flux 的 API 服务中。你将通过服务，GPU Spark 运行时间和路由器进行所有三个层次的工作。你将做的是：·设计，构建和操作 Kubernetes 上托管的 Spark 服务控制飞机：Java REST API,Spark Connect 运行器，Kyuubi 以及使用 Helm 图表和 Flux 的部署。· 扩大 cuDF Spark 运行时间和 CPU/GPU 工作负载路由器在 Scala 和 Java 中，包括与 Delta Lake,Apache Iceberg 和 Unity Catalog 的互操作性 · 与客户团队和上游图书馆团队一起调查运行的超过一千个同步工作集群中的生产故障，并推动解决方案到关闭 · Inst
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NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. 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 is seeking a Senior Systems Software Engineer for the Apache Spark Acceleration group. GPU accelerated data processing has moved from proof of concept to production deployments. Enterprises now recognize the need for accelerated computing to handle large data processing needs. Multi-node GPU deployments reduce cloud computing costs and lower the latency of batch ETL workloads. At NVIDIA, we accelerate Apache Spark with an open source plugin that speeds up Spark applications on GPUs without code changes, and our cuDF Spark library is integrated with AWS EMR, Databricks, Google Dataproc, Oracle Cloud Data Flow, Bytedance Volcengine, Tencent Cloud and Cloudera. This role is on the team that runs that acceleration as a handled Spark service inside NVIDIA. The service accomplishes production data pipelines for NVIDIA’s internal data platform at thousands of jobs an hour on Kubernetes and AWS, under a customer SLA. It packages the cuDF Spark plugin and a CPU/GPU workload router into an API-based service built on Spark Connect, Kyuubi, Helm and Flux. You will work across all three layers: the service, the GPU Spark runtime, and the router.
What you’ll be doing:
- Design, build and operate hosted Spark service control plane on Kubernetes: the Java REST API, the Spark Connect runner, Kyuubi, and deployment using Helm charts and Flux
- Own code review for one or more services end to end and keep them releasable on the release train
- Extend the cuDF Spark runtime and the CPU/GPU workload router in Scala and Java, including interoperability with Delta Lake, Apache Iceberg and Unity Catalog
- Investigate production failures on clusters running more than a thousand concurrent jobs together with the customer team and upstream library teams, and drive fixes to closure
- Instrument metrics, dashboards and alerts; take part in the on-call rotation and keep the runbooks current
- Provide recommendations and feedback to teams regarding decisions surrounding topics such as infrastructure, continuous integration and testing strategy
What we need to see:
- BS, MS, or PhD in Computer Science, Computer Engineering, or a closely related field (or equivalent experience)
- 9+ years of experience in software development
- Strong distributed-systems fundamentals and proficiency in Java or Scala, plus C++ or Python
- Hands-on experience operating services on Kubernetes, on-premise or cloud
- Experience owning or reviewing a long-lived server: REST front ends, proxies or request routers, JDBC or Thrift services
- Experience supporting enterprise or internal production customers, including on-call
- Experience using AI tools in software development
Ways to stand out from the crowd:
- Apache Spark internals, Spark Connect, or Kyuubi
- Delta Lake, Apache Iceberg or Unity Catalog integration work
- GPU data processing with cuDF, or CUDA experience
- Significant contributions to data platform projects committed to collaboration and shared development (Apache Spark, Velox, Presto, Apache Arrow, Apache DataFusion)
Widely Is considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 23, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Originally posted on Himalayas