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Cuda Engineer Jobs in California (NOW HIRING)

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Cuda Engineer information

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$36K

$105.9K

$135.7K

How much do cuda engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for cuda engineer in California is $105,877.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,300.00 and $134,200.00 per year, depending on experience, location, and employer.

What is a CUDA engineer?

CUDA Engineers are software developers who specialize in using NVIDIA's CUDA (Compute Unified Device Architecture) platform to write programs that run on Graphics Processing Units (GPUs). They optimize and accelerate computational tasks by parallelizing code, making use of GPUs’ capabilities for high-performance computing. CUDA Engineers often work in fields like machine learning, scientific computing, and graphics, where large amounts of data need to be processed quickly. Their expertise includes proficiency in C/C++, CUDA programming, and understanding GPU hardware and parallel computing concepts.

What are the key skills and qualifications needed to thrive as a CUDA engineer?

To thrive as a CUDA Engineer, you need a strong proficiency in C/C++ programming, parallel computing concepts, and deep knowledge of GPU architectures, often supported by a computer science or engineering degree. Experience with NVIDIA CUDA Toolkit, profiling/debugging tools, and sometimes certifications like NVIDIA DLI are highly valuable. Strong problem-solving, attention to detail, and effective communication skills help you optimize code and collaborate across teams. These skills ensure efficient development of high-performance GPU applications and successful project delivery in compute-intensive fields.

What are some common challenges faced by CUDA engineers when optimizing GPU-accelerated applications?

CUDA Engineers frequently encounter challenges such as managing memory effectively between the host and the device, optimizing kernel performance, and minimizing data transfer bottlenecks. Debugging parallel code can also be complex due to race conditions and the difficulty of reproducing timing-related bugs. Collaborating closely with software developers and data scientists is essential to ensure that GPU resources are leveraged efficiently and that the application's overall performance meets project goals.

What is the difference between Cuda Engineer vs GPU Developer?

AspectCuda EngineerGPU Developer
Required CredentialsBachelor's or Master's in Computer Science, Engineering, or related; knowledge of CUDA, C++, parallel programmingBachelor's or Master's in Computer Science, Engineering, or related; experience with GPU programming, CUDA, OpenCL
Work EnvironmentResearch labs, tech companies, hardware firms focusing on GPU accelerationSoftware development teams, gaming, AI, scientific computing sectors
Employer & Industry UsageHardware manufacturers, AI companies, high-performance computing firmsGame development, scientific research, machine learning applications

While both roles involve GPU programming and CUDA expertise, a Cuda Engineer primarily focuses on developing and optimizing CUDA-based solutions for hardware acceleration. In contrast, a GPU Developer works on broader GPU programming tasks, including application development across various platforms. The roles often overlap but differ in scope and specific focus areas.

What are popular job titles related to Cuda Engineer jobs in California?

For Cuda Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Cuda Engineer jobs in California look for?

The top searched job categories for Cuda Engineer jobs in California are:

What cities in California are hiring for Cuda Engineer jobs?

Cities in California with the most Cuda Engineer job openings:

Cuda Engineer jobs near you
Infographic showing various Cuda Engineer job openings in California as of August 2026, with employment types broken down into 95% Full Time, 2% Part Time, and 3% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $105,877 per year, or $50.9 per hour.

Technical Marketing Engineer - CUDA-Q Developer Enablement

Nvidia Corporation

Santa Clara, CA • On-site

Full-time

Re-posted 20 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies

Job description

NVIDIA is building the leading platform for Quantum Computing with CUDA-Q, and we need technical marketing engineers who can bring it to the developers, researchers, and AI agents who will use it. In this role, you will drive technical enablement across a broad developer ecosystem - creating content, tools, and experiences that help quantum researchers, HPC practitioners, and AI developers get hands-on with CUDA-Q. You will work at the intersection of quantum computing, accelerated computing, and AI to ensure that the people building the next generation of quantum applications have everything they need to succeed.
What you'll be doing:
  • Analyze developer journey needs with product teams and domain experts to identify and close gaps for both human and agent workflows using CUDA-Q
  • Define practical standards for developer surfaces including GitHub, docs, example code, and onboarding that work for both developers and the AI agents they use
  • CreateMCP servers, Agent Skills, API documentation patterns, agent-consumable tests, and prompt-ready templates
  • Build and maintain enablement resources - templates, runbooks, checklists, context files, and reference implementations - that quantum researchers and developers can use directly
  • Evaluate content performance using human engagement metrics and agent signals to continuously improve developer time-to-value with CUDA-Q
  • Define success criteria and evaluation frameworks for agentic developer tools - designing benchmarks, running evals, and translating results into actionable product improvements
  • Track emerging AX, GEO, and AI citation research and translate findings into practical guidance for teams building quantum computing applications

What we need to see:
  • Bachelor's degree in a technical field, or equivalent experience
  • 5+ years work of related work experience
  • Experience with documentation systems, information architecture, and content strategy for developer-facing and agent-facing technical content
  • Understanding of agent-consumable content standards such as llms.txt, MCP, Agent Skills, and API documentation patterns
  • Knowledge of quantum computing concepts and familiarity with CUDA-Q or similar quantum computing frameworks
  • Proficiency with agentic coding harnesses such as Claude Code or Codex, and the judgment to evaluate AX tooling - from MCP servers and Agent Skills to API docs and prompt templates - for different contexts
  • Strong communication and interpersonal skills, with the ability to collaborate effectively with researchers, engineers, and product teams
  • Experience designing evaluations for developer or ML products - controlled experiments, human eval pipelines, or benchmark harnesses - with clear success criteria defined upfront
  • A track record of staying ahead of fast paced technology shifts and translating findings into practical guidance before it becomes conventional wisdom

Ways to stand out from the crowd:
  • Hands-on experience with CUDA-Q or other quantum computing frameworks, and an intuition for how quantum workloads connect to the broader GPU-accelerated computing stack
  • Track record of building enablement resources - libraries, playbooks, templates - that developer teams actually use, and driving adoption across organizations
  • Contributions to open-source quantum computing, AI, or developer tooling projects
  • Experience using data and analytics to measure developer onboarding, identify friction points, and drive improvements

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and talented people in the world working with us. If you are creative, autonomous, and passionate about building open-source tools that make AI safer and more private, 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 136,000 USD - 212,750 USD for Level 3, and 160,000 USD - 253,000 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until July 5, 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

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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

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