Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Software Development @ 7
Scala @ 6
Spark @ 4
ETL @ 4
Java @ 6
Distributed Systems @ 4
Parquet @ 4
Presto @ 3
JSON @ 4
CUDA @ 4
Cloud Computing @ 4
GPU @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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.
NVIDIA is seeking a Sr. Systems Software Engineer for the Apache Spark Acceleration group. Over the past five years GPU accelerated data processing has moved from proof of concept to production deployments. Many enterprises recognize accelerated computing is vital to handle their large data processing needs. Multi-node GPU deployments will reduce cloud computing costs and lower latency in batch ETL workloads. Apache Spark is the most popular data processing engine in data centers. At NVIDIA, we are developing an open source plugin to accelerate Spark applications on GPUs without any code changes.
Responsibilities
- Enable C++ native execution of Spark operations on CUDA
- Develop CUDA/C++ libraries to accelerate DataFrames and I/O operations on common file formats such as Parquet, ORC and JSON
- Collaborate with distributed systems teams to craft solutions to distributed processing problems and challenges at large scale
- Work with open source communities to enhance libraries like RAPIDS, CCCL and UCX through technical discussion and code contributions
- Provide recommendations and feedback to teams regarding decisions surrounding topics such as infrastructure, continuous integration and testing strategy
- Build, test and optimize across different platforms
Requirements
- 9+ years of experience in software development
- 5+ years hands on experience with data platform development
- BS/MS/PhD in computer science or a related field (or equivalent experience)
- Proficiency in C++, Java, Scala
- Experience supporting enterprise customers
- Familiarity with the open source data platform ecosystem is a plus (Apache Spark, Velox, Presto, Apache Arrow, Apache DataFusion, etc.)
- Experience using AI tools in software development
Compensation and Other Details
- Base salary range: 184,000 USD - 287,500 USD for Level 4
- Base salary range: 224,000 USD - 356,500 USD for Level 5
- You will also be eligible for equity and benefits. (link provided in original posting)
- Applications for this job will be accepted at least until January 24, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. The company does not discriminate on the basis of protected characteristics.