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$85

How much do hourly cuda jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for hourly cuda in the United States is $39.36, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $57.45 per hour, depending on experience, location, and employer.

What is the difference between Hourly Cuda vs Hourly Data Analyst?

AspectHourly CudaHourly Data Analyst
Required CredentialsCUDA programming certification, technical skillsDegree in Data Science, Statistics, or related field
Work EnvironmentTech companies, research labs, GPU-focused projectsBusiness, finance, healthcare, and tech industries
Employer & Industry UsageTech firms utilizing GPU computingOrganizations analyzing data for insights
Common Search & ComparisonYesYes

Hourly Cuda professionals focus on GPU programming and parallel computing, often requiring technical certifications. Hourly Data Analysts interpret data to inform business decisions, typically with a degree in related fields. While both roles involve technical skills, they serve different industry needs and environments.

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Hourly Cuda jobs near you
Infographic showing various Hourly Cuda job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 51% Full Time, 44% Part Time, 1% Temporary, and 3% Contract. Highlights an 97% Physical, and 3% Remote job distribution, with an average salary of $81,860 per year, or $39.4 per hour.

NVIDIA 2027 Internships: Ph.D. Research Hardware

Santa Clara, CA • On-site

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidiaexternal

Internship

Posted 21 days ago

Key responsibilities

  • Design and implement novel approaches to circuit and VLSI design, including ASIC development and advanced EDA methodologies.

  • Collaborate with team members, other teams, and external researchers.

  • Transfer research to product groups to enable new products or types of products.

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

Job description

By submitting your resume, you acknowledge that your Ph.D. Research Hardware internship application will be processed in accordance with NVIDIA's Applicant Privacy Policy and you agree to our Terms of Service. We'll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities

NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society - from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create. Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading Hardware teams.

We're seeking strategic, ambitious, hard-working, collaborative, and creative individuals who are passionate about helping us tackle challenges no one else can solve. Learn more about Research at NVIDIA. What you will be doing: Design and implement novel approaches to circuit and VLSI design, including ASIC development and advanced EDA methodologies.

Collaborate with other team members, teams, and/or external researchers. Transfer your research to product groups to enable new products or types of products. Deliverable results include prototypes, patents, products, and/or publishing original research.

What we need to see: Must be actively enrolled in a university pursuing a Ph.D. degree in Computer Science, Electrical Engineering, or a related field, for the full duration of the internship; anticipated graduation date (month and year) must be clearly indicated on a resume or CV to be considered. Depending on the internship, prior experience or knowledge requirements could include the following programming skills and technologies: Python, C, C++, Perl, MATLAB, CUDA, Verilog, SystemVerilog, CAD tool packages (e.g., Cadence, Synopsys, HFSS), ML Frameworks (e.g., PyTorch), EDA tools Strong background in research with publications at top conferences and/or patents

Excellent communication and collaboration skills. Potential internships require research experience in at least one of the following areas: Circuit Design PLLs and Clocking Circuits SerDes and High-Speed Signaling Integrated Photonics and Optical Interconnects SRAMs, Memory Design, and Cache Architectures Power Delivery/Regulation Security Circuits and Hardware Security High-Speed Logical Design Novel Digital VLSI Circuits ASIC and VLSI ASIC and VLSI Design Techniques ML Accelerators Hardware/software co-design Electronic Design Automation GPU accelerated EDA Agent for Hardware Design Click here to learn more about NVIDIA, our early talent programs, benefits offered to students and other helpful student resources related to our latest technologies and endeavors. Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience.

The hourly rate for our interns is 38 USD - 94 USD. You will also be eligible for Intern benefits. Applications are accepted on an ongoing basis.

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

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