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Assistant Cuda Jobs in Oregon (NOW HIRING)

What you will be doing: Assist independent software vendors, ecosystem partners, and lighthouse ... CUDA, multi-physics solvers, or AI surrogate models. Success enabling partner solutions or building ...

Assistant Cuda information

What are the roles and responsibilities of an assistant CUDA developer?

An Assistant Cuda typically supports senior CUDA (Compute Unified Device Architecture) developers or teams working with NVIDIA’s parallel computing platform. Their responsibilities include assisting in developing, testing, and optimizing code written for GPUs to accelerate computing tasks, debugging CUDA applications, and maintaining documentation. They may also handle routine tasks such as performance benchmarking, code reviews, and collaborating with other team members to implement efficient GPU solutions. This role is crucial in organizations that rely on high-performance computing, scientific simulations, or AI workloads.

What skills and qualifications are needed to thrive as an assistant CUDA developer?

To thrive as an Assistant CUDA Developer, you need strong programming skills in C/C++, a solid understanding of parallel computing concepts, and familiarity with GPU architectures, often backed by a degree in computer science or a related field. Proficiency with CUDA development tools, debugging utilities, and version control systems like Git is typically required. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for collaborating with teams and optimizing code. These skills ensure efficient development of high-performance applications and successful integration of GPU acceleration into software solutions.

What are common challenges faced by assistant CUDA developers when optimizing code for GPU performance?

Assistant CUDA developers often encounter challenges such as managing memory efficiently between the host and device, ensuring proper kernel parallelization, and avoiding thread divergence. Balancing occupancy and resource usage can also be tricky, as it requires a deep understanding of how CUDA schedules and executes threads. Collaborating closely with data scientists and other engineers is essential to identify performance bottlenecks and implement effective optimizations.

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

AspectAssistant CudaAssistant Data Analyst
Required CredentialsTypically a relevant degree in computer science or related fieldOften a degree in data science, statistics, or related field
Work EnvironmentTech companies, software development teams, AI projectsBusiness, finance, marketing, or research departments
Employer & Industry UsageUsed in tech and AI industries for supporting CUDA programming tasksCommon in data-driven industries for data processing and analysis

Assistant Cuda and Assistant Data Analyst roles share some technical background but differ mainly in focus. Assistant Cuda primarily supports GPU programming and AI development, while Assistant Data Analyst focuses on data interpretation and reporting. Both roles require relevant technical skills and are found in industries leveraging data and technology, but their daily tasks and industry applications vary significantly.

What are the most commonly searched types of Cuda jobs in Oregon?

The most popular types of Cuda jobs in Oregon are:

What are popular job titles related to Assistant Cuda jobs in Oregon?

For Assistant Cuda jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Assistant Cuda jobs in Oregon look for?

The top searched job categories for Assistant Cuda jobs in Oregon are:

Solutions Architect, Physical AI and Omniverse

OR • On-site, Remote

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees

Full-time

Posted 11 days ago


Key responsibilities

  • Assist partners and customers in assessing and adopting technologies within DSX Sim and Omniverse libraries.

  • Architect and demonstrate simulation workflows to help build, validate, optimize, and operationalize AI factory digital twins.

  • Collaborate with partners to build and validate simulation-ready asset pipelines using OpenUSD, SimReady specifications, and multi-physics simulation.


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

NVIDIA is a leader in accelerated computing, artificial intelligence, and next-generation platform innovation. Our Worldwide Field Operations Solutions Architecture team supports third-party software vendors, partners, and customers. We transform advanced technologies into practical, repeatable solutions.

We are hiring a Solutions Architect to boost adoption of NVIDIA DSX Sim, Omniverse libraries, and AI agent skills. This position will establish DSX Sim as a shared, simulation-ready decision layer for AI factory creation. We also provide partners with actionable methods to embed accelerated rendering, physics, storage, streaming, and user interface capabilities into their applications.

This role connects customer demands with field delivery and product engineering, improving how AI factories and industrial digital twins are developed, validated, and put into operation. What you will be doing: Assist independent software vendors, ecosystem partners, and lighthouse customers in assessing and adopting technologies within DSX Sim, and Omniverse libraries. Architect and demonstrate simulation workflows that help customers build, validate, optimize, and operationalize AI factory digital twins.

Collaborate with partners to build and validate simulation-ready asset pipelines using OpenUSD, SimReady specifications, engineering data, multi-physics simulation, and operational inputs. Drive incorporation of Omniverse libraries (ovRTX, ovPhysx, ovStorage, usd-agents, etc) into partner applications, services, and enterprise workflows. Develop reusable reference architectures, demonstrations, sample workflows, benchmarks, and proof-of-concept evaluations that address customer challenges.

Translate technical and business requirements into clear solution plans while coordinating with sales, product engineering, developer relations, and partner teams to resolve blockers and advance adoption. Gather field insights, advocate for partner needs, and contribute technical mentorship that improves product direction, enablement resources, and team execution. What we need to see: Bachelor's degree in computer science, engineering, or a related technical field, or equivalent experience.

2+ years of relevant engineering, technical sales, or solution architecture experience; candidates considered for the higher level typically bring 5+ years of related experience. A solid base in one or more relevant areas, such as computer graphics, physically based rendering, physics simulation, engineering simulation, digital twins, or accelerated computing. Practical understanding of three-dimensional workflows and asset pipelines through OpenUSD or similar scene-description, modeling, and data-interchange technologies.

Experience programming in Python and a higher-level language such as C, C++, or Java. Hands-on success developing technical prototypes, setting up evaluations, benchmarking solutions, or supporting customer implementations of external libraries. Ability to manage technical relationships, explain sophisticated concepts clearly, and work closely with developers at external software companies, NVIDIA partners, and internal collaborators.

Ways to stand out from the crowd: OpenUSD certification or substantial hands-on work with OpenUSD composition, schemas, validation, optimization, or asset-pipeline development. Background crafting digital twins or simulation workflows for AI factories, data centers, architecture and engineering, industrial systems, or other complex physical environments. Knowledge of high-performance rendering techniques, physics, and simulation technologies such as NVIDIA RTX, PhysX, CUDA, multi-physics solvers, or AI surrogate models.

Success enabling partner solutions or building workflows such as computer-aided-design conversion, synthetic data generation, defect detection, neural reconstruction, or simulation-ready asset creation. 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 July 20, 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.


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Benefits

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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