NVIDIASenior Systems Software Engineer - Accelerated Spark Applications
NVIDIA is hiring a Senior Systems Software Engineer - Accelerated Spark Applications. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Works on AI ●●●○ is how Level rates this software engineer role: the daily work is on AI products, without building the model.
- The listed pay starts 9% above the typical software engineer posting on Level.
- Tools and skills the posting cites include Databricks, Kubernetes and AWS.
- Level lists 2,700+ other open roles at NVIDIA.
- The role was posted within the past week.
AI in this role
Design and operate a hosted Apache Spark acceleration service on Kubernetes for GPU-based data processing workloads.
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.
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.How we rate this
Senior Systems Software Engineer - Accelerated Spark Applications at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- This job starts at
- $184k
- Typical software engineer job
- $168k
This posting starts 9% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where cloud computing was part of your work. What did you do?
- Tell me about a project where rest api was part of your work. What did you do?
- Walk me through how you've used Databricks in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Distributed Systems, ETL, Cloud Computing, REST API, and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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