Role at a glance
- Job function
-
Software Engineering & IT Software Engineering
- Salary
- Not yet verified Check the description for pay details; an amount or pay period has not been verified.
- Location
- Champaign, Illinois, United States
- Employment
- Full-time
- Experience
- Senior Level 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)
- Education
- BS, MS, or PhD in Computer Science, Computer Engineering, or a closely related field (or equivalent experience)
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Role Summary
The Senior Systems Software Engineer works across NVIDIA’s hosted Spark service, GPU Spark runtime, and CPU/GPU workload router. The service runs production data pipelines on Kubernetes and AWS, packaging the cuDF Spark plugin and workload router as an API-based service.
What You'll Do
- Design, build, and operate the hosted Spark service control plane on Kubernetes, including its Java REST API, Spark Connect runner,...
- 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 CPU/GPU workload router in Scala and Java, including interoperability with Delta Lake, Apache Iceberg,...
- Investigate production failures on clusters running more than a thousand concurrent jobs with customer and upstream library teams, and...
- Instrument metrics, dashboards, and alerts; participate in the on-call rotation and maintain runbooks.
- Provide recommendations and feedback to teams on infrastructure, continuous integration, and testing strategy.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
A BS, MS, or PhD in Computer Science, Computer Engineering, or a closely related field, or equivalent experience. Requires distributed-systems fundamentals; proficiency in Java or Scala, plus C++ or Python; hands-on experience operating Kubernetes services; experience with long-lived servers and production customers, including on-call; and experience using AI tools in software development.
Preferred
- 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,...
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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 www.nvidiabenefits.com/
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.
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.