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Internship Cuda Programmer Jobs in Seattle, WA (NOW HIRING)

NVIDIA

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

... GPU architecture • CUDA or OpenCL programming experience • Experiences in systems with ... and interns is a bonus Company : NVIDIA is a computing platform company operating at the ...

NVIDIA AI

Senior Robotics Research Scientist

Seattle, WA · On-site

$112K - $142K/yr

... world impact; • Mentoring interns and more junior research scientists and engineers ... C++, CUDA, and Warp • Prior experience working with product managers and engineering teams to ...

Amazon

Software Dev Engineer, EC2 Nitro

Seattle, WA · On-site

$159K/yr

Your impact will extend from low-level systems (CUDA, EFA, firmware) through ML frameworks to ... BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ ...

Nvidia

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

CUDA or OpenCL programming experience. * Experiences in systems with constrained resources, such as ... A track record of success in mentoring junior engineers and interns is a bonus. With highly ...

Nvidia

Senior Robotics Research Scientist

Seattle, WA · On-site

$112K - $142K/yr

Mentoring interns and more junior research scientists and engineers. What we need to see: * A PhD ... Exceptional programming skills in Python; in addition, familiarity with C++, CUDA, and Warp is a ...

CoreWeave

Software Engineer, Inference AI/ML

Bellevue, WA · On-site

$92K - $135K/yr

Internship or project that deployed a microservice or ML inference demo. * Coursework/research with ... CUDA projects a plus. * Familiarity with Grafana/Prometheus/OpenTelemetry or similar tooling. Why ...

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Internship Cuda Programmer information

See Seattle, WA salary details

$12

$45

$81

How much do internship cuda programmer jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for internship cuda programmer in Seattle, WA is $45.37, according to ZipRecruiter salary data. Most workers in this role earn between $17.50 and $65.38 per hour, depending on experience, location, and employer.

What is the difference between Internship Cuda Programmer vs Cuda Developer?

AspectInternship Cuda ProgrammerCuda Developer
CredentialsEnrolled in or recent graduate of Computer Science or related fieldBachelor's or higher in Computer Science, with experience in CUDA programming
Work EnvironmentInternship setting, learning-focused, entry-level projectsFull-time professional role, developing complex GPU-accelerated applications
Industry UsageResearch labs, tech companies, internships for skill developmentTech firms, gaming, scientific computing, high-performance computing

While an Internship Cuda Programmer is typically a learning position for students or recent graduates gaining foundational experience, a Cuda Developer is a full-time professional responsible for designing and optimizing GPU-accelerated software. The roles differ mainly in experience level, responsibilities, and career stage, but both require knowledge of CUDA programming and GPU architecture.

What are the most commonly searched types of Cuda Programmer jobs in Seattle, WA? The most popular types of Cuda Programmer jobs in Seattle, WA are:
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Internship Cuda Programmer jobs near you

Senior Deep Learning Compiler Engineer

NVIDIA

Redmond, WA • On-site

$117K - $160K/yr

Full-time

Re-posted 8 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies

Job description

Job Summary:
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. They are seeking a Deep Learning Compiler Engineer to analyze deep learning networks and develop compiler optimization algorithms, collaborating with various teams to enhance deep learning software performance.
Responsibilities:
• Analyzing deep learning networks and developing compiler optimization algorithms.
• Collaborating with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software.
• Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler infrastructure techniques for neural networks, and other general software engineering work.
Qualifications:
Required:
• Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience
• 3+ years of relevant work or research experience in performance analysis and compiler optimizations
• Ability to work independently, define project goals and scope, and lead your own development efforts
• Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design
• Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team
Preferred:
• Proficient in CPU and/or GPU architecture
• CUDA or OpenCL programming experience
• Experiences in systems with constrained resources, such as embedded platforms, small memory size, and cross compilation
• Experience with the following technologies: MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as PyTorch
• GPU kernel generation with high performance and fast build time
• A track record of success in mentoring junior engineers and interns is a bonus
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

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

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