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Entry Level Cuda Jobs in Seattle, WA (NOW HIRING)

Experience in developing CUDA, DirectX, OpenGL/Vulkan applications NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and ...

Entry Level Cuda information

What is an entry level CUDA job?

Entry-level CUDA jobs are positions designed for individuals who are new to working with CUDA, NVIDIA’s parallel computing platform and programming model. These roles typically involve assisting in developing, optimizing, and debugging GPU-accelerated applications using languages such as C or C++. Candidates are expected to have a basic understanding of parallel programming concepts and the fundamentals of GPU architectures. Entry-level CUDA professionals often work under the guidance of senior developers to contribute to projects in fields like machine learning, scientific computing, or computer graphics.

What are some common challenges faced by entry level CUDA developers when starting in this role?

Entry-level CUDA developers often encounter challenges such as understanding parallel programming concepts and efficiently optimizing code for GPU architectures. Adjusting to the differences between CPU and GPU processing, especially in terms of memory management and thread synchronization, can be a steep learning curve. Collaboration with more experienced developers and regularly reviewing code can help newcomers overcome these hurdles and accelerate their mastery of CUDA development.

What are the key skills and qualifications needed to thrive as an entry level CUDA developer, and why are they important?

To thrive as an Entry Level CUDA Developer, you need a solid understanding of parallel programming, C/C++ programming skills, and a degree in computer science or a related field. Familiarity with NVIDIA CUDA Toolkit, GPU architectures, and version control systems like Git is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate and troubleshoot efficiently. These competencies are crucial for developing high-performance GPU-accelerated applications and contributing to team success in computational projects.

What is the difference between Entry Level Cuda vs Entry Level Data Analyst?

AspectEntry Level CudaEntry Level Data Analyst
Required CredentialsCUDA programming knowledge, basic understanding of GPU computingBasic statistics, Excel, SQL, possibly some programming (Python, R)
Work EnvironmentTech companies, research labs, industries utilizing GPU accelerationBusiness, finance, marketing, tech firms analyzing data
Industry UsageHigh in AI, machine learning, scientific computingBroad across various sectors for data-driven decision making
Common Search/ComparisonYesYes

Entry Level Cuda roles focus on GPU programming and parallel computing, often in tech and research environments. Entry Level Data Analyst positions involve data interpretation, reporting, and basic analytics skills across multiple industries. While both are entry-level, Cuda roles require technical GPU knowledge, whereas Data Analyst roles emphasize data handling and visualization skills.

Are entry level CUDA programmers in demand?

Entry level CUDA programmers are in demand in industries such as gaming, scientific computing, and artificial intelligence, where GPU acceleration is essential. Knowledge of parallel programming, CUDA tools, and basic understanding of GPU architecture can improve job prospects, especially as demand for high-performance computing grows.

What are the most commonly searched types of Cuda jobs in Seattle, WA?

The most popular types of Cuda jobs in Seattle, WA are:

GPU Compiler Engineer

Nvidia

Redmond, WA

Full-time

Re-posted 12 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

7th of 246 rated software companies


Job description

We are searching for a Backend Compiler Engineer for an exciting and fun role in our GPU Software organization. Our Compiler team is responsible for constructing and emitting the highest performance GPU machine instructions for Graphics (OpenGL, Vulkan, DX) and Compute (CUDA, PTX, OpenCL, Fortran, C++). This team is comprised of worldwide leading compiler engineering experts who provide leading edge performance and capabilities for NVIDIA's current and future complex parallel SIMT architectures.

What you will be doing:

  • Understand, modify, and improve an NVIDIA proprietary GPU compiler backend written in C++

  • Design and develop new compiler passes and optimizations to produce best-in-class, robust, supportable compiler and tools

  • Work with global compiler, hardware and application teams to oversee improvements and problem resolutions

  • Be part of a team that is at the center of deep-learning compiler technology spanning architecture design and support through functional languages

What we need to see:

  • B.S. or degree in Computer Science/Engineering or equivalent experience

  • 2+ years of compiler code generation experience

  • Excellent hands-on C++ programming skills

  • Strong background in software engineering principles with a focus on crafting robust and maintainable solutions to challenging problems

  • Good communication and documentation skills and self-motivated

Ways to stand out from the crowd:

  • M.S./PhD. with significant compiler related project or thesis work preferred

  • Background in LLVM code generation including instruction scheduling, software pipelining, register allocation, GlobalISel, TableGen, LLVM IR, and Machine IR (MIR)

  • Experience in developing CUDA, DirectX, OpenGL/Vulkan applications

NVIDIA's invention of the GPU 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. Today, we are increasingly known as "the AI computing company".

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Deep Learning, Artificial Intelligence, Autonomous Vehicles, Virtual Reality, etc. Our diverse team of talented, capable, and professional people are our greatest asset! If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 25, 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Nvidia

Sourced by ZipRecruiter

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.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993