ZipRecruiter

Log In

1

Nvidia Engineering Jobs in Illinois (NOW HIRING)

Nvidia

Principal Systems Software Engineer

Champaign, IL · On-site

$135K - $181K/yr

NVIDIA is seeking a Sr. Principal Systems Software Engineer for the Apache Spark Acceleration group. GPU accelerated data processing has moved from proof of concept to production deployments.

Nvidia

Principal Systems Software Engineer

Champaign, IL

$135K - $181K/yr

NVIDIA is seeking a Sr. Principal Systems Software Engineer for the Apache Spark Acceleration group. GPU accelerated data processing has moved from proof of concept to production deployments.

Nvidia

Senior System Software Engineer

Champaign, IL

$122K - $161K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... NVIDIA is seeking a Sr. Systems Software Engineer for the Apache Spark Acceleration group. Over the ...

Nvidia

Senior System Software Engineer

Champaign, IL · On-site

$122K - $161K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... NVIDIA is seeking a Sr. Systems Software Engineer for the Apache Spark Acceleration group. Over the ...

YO AI Labs

CUDA Engineering Expert - Remote

Chicago, IL · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

next page

Showing results 1-20

All JobsNvidia Engineering JobsNvidia Engineering Jobs in Illinois

Nvidia Engineering information

See Illinois salary details

$45.1K

$142.3K

$168.6K

How much do nvidia engineering jobs pay per year?

As of Sep 6, 2026, the average yearly pay for nvidia engineering in Illinois is $142,319.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,900.00 and $167,600.00 per year, depending on experience, location, and employer.

What is an Nvidia engineer?

An Nvidia Engineering job involves designing, developing, and optimizing hardware or software solutions in areas such as graphics processing, AI, and high-performance computing. Engineers at Nvidia work on cutting-edge technologies, including GPUs, deep learning frameworks, and system architecture. Roles vary from hardware design and verification to software development and AI research, depending on expertise. Strong skills in programming, computer architecture, and problem-solving are typically required.

What types of projects do Nvidia engineers typically work on, and how is teamwork structured within the engineering department?

Nvidia Engineers commonly engage in projects related to GPU development, AI and deep learning solutions, software driver optimization, and next-generation hardware innovation. Project teams are often multidisciplinary, bringing together software, hardware, and systems engineers to collaborate closely on end-to-end product development. Engineers frequently work in agile, fast-paced environments, attend regular team stand-ups, and participate in cross-functional meetings. This collaborative structure fosters creativity, accelerates problem-solving, and ensures high-quality product delivery while offering team members exposure to diverse technologies and career growth opportunities.

What are the key skills and qualifications needed to thrive as an Nvidia engineer, and why are they important?

To thrive in Nvidia Engineering, candidates typically need strong proficiency in computer engineering, software development, and a solid understanding of hardware architecture, often backed by a relevant degree such as Electrical Engineering or Computer Science. Familiarity with tools like CUDA, C/C++, Python, and version control systems, as well as experience with GPU programming, are highly valued, and certifications such as Nvidia's Deep Learning Institute credentials can enhance a candidate's profile. Excellent problem-solving, team collaboration, and communication skills set top performers apart in this role. These skills and qualifications enable engineers to contribute effectively to complex, innovative projects that drive Nvidia's technological advancements.

What are the most commonly searched types of Nvidia Engineering jobs in Illinois?

The most popular types of Nvidia Engineering jobs in Illinois are:

What are popular job titles related to Nvidia Engineering jobs in Illinois?

For Nvidia Engineering jobs in Illinois, the most frequently searched job titles are:

What job categories do people searching Nvidia Engineering jobs in Illinois look for?

The top searched job categories for Nvidia Engineering jobs in Illinois are:

What cities in Illinois are hiring for Nvidia Engineering jobs?

Cities in Illinois with the most Nvidia Engineering job openings:

Nvidia Engineering jobs near you
Infographic showing various Nvidia Engineering job openings in Illinois as of August 2026, with employment types broken down into 94% Full Time, 3% Part Time, 2% Contract, and 1% Nights. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $142,319 per year, or $68.4 per hour.

Principal Systems Software Engineer - NVIDIA

Experience Champaign Urbana

Champaign, IL • On-site

$272 - $431/hr

Other

Posted 7 days ago

Key responsibilities

  • Develop Java, Scala, and CUDA/C++ libraries to accelerate DataFrames and I/O operations on common file formats such as Parquet, ORC, and JSON.

  • Work with open source communities to enhance libraries like NVIDIA cuDF, CCCL, and UCX through technical discussion and code contributions.

  • Collaborate with distributed systems teams to craft solutions to distributed processing problems at large scale.

Job description

NVIDIA is a global leader in accelerated computing. It designs graphics processing units (GPUs) and chip units for mobile computing, automotive, gaming, and professional markets.


NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.


Please see the Research Park Tenant Directory for more information. NVIDIA – Research Park


About the role


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 are now recognizing the needs of accelerated computing to handle their large data processing needs. Multi-node GPU deployments will reduce cloud computing costs and lower latency batch ETL workloads.


At NVIDIA, we have been invested in accelerating Apache Spark, providing an open source plugin for Apache Spark. Apache Spark is the most popular data processing engine in data centers. We strive to accelerate Spark applications on GPUs without any code changes. We are passionate about working on hard problems that have an impact. You will need to have strong programming skills, a deep understanding of software development related to C++. You will work with a team that is using open source libraries like RAPIDS to accelerate reading, writing and batch data operations in Spark.


Requirements

  • BS, MS, or PhD in Computer Science, Computer Engineering, or closely related field (or equivalent experience)

  • 15+ years of work experience in software development

  • Outstanding technical skills in designing and implementing high-quality distributed systems

  • Excellent programming skills in C++, Java, and/or Scala

  • Ability to work with teams across organizational boundaries and geographies

  • Familiarity with the open source data platform ecosystem (Apache Spark, Velox, Presto, Apache Arrow, Apache DataFusion, etc.). Meaningful contributions to the OSS community a plus.

  • Highly motivated with strong interpersonal skills

  • Database query optimization is a strong plus


Responsibilities

  • Develop Java, Scala and CUDA/C++ libraries to accelerate DataFrames and I/O operations on common file formats such as Parquet, ORC and JSON

  • Enable interoperability with table formats such as Apache Iceberg and Delta Lake, and metastores such as Unity Catalog

  • Work with open source communities to enhance libraries like NVIDIA cuDF, CCCL and UCX through technical discussion and code contributions

  • Collaborate with distributed systems teams to craft solutions to distributed processing problems challenges at large scale

  • Provide recommendations and feedback to teams regarding decisions surrounding topics such as infrastructure, continuous integration and testing strategy

  • Build, test and optimize CUDA/C++ libraries across different platforms


Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD – 431,250 USD.


You will also be eligible for equity and benefits.


Applications for this job will be accepted at least until July 19, 2026.

#J-18808-Ljbffr

Apply