GPU C++ Modeling Engineer - New College Grad 2026 at NVIDIA

Shanghai, China

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Not SpecifiedCompensation

Entry Level & New GradExperience Level

Full TimeJob Type

UnknownVisa

Semiconductors, AI, GraphicsIndustries

Requirements

In depth knowledge of computer architecture, with good understanding of modern ISA and microprocessor implementation techniques
Good understanding of GPU concept and pipeline, in terms of Graphics processing and parallel compute
Good mastery of C++ language
BSEE, BSCSE, or equivalent required. MS or PhD is a plus
Experience of performance/functional modelling, profiling and analysis is a plus
Experience with trace-driven and execution-driven simulation model development is a plus

Responsibilities

Investigate and propose architecture ideas based on quantitative study of existing and projected GPU architecture
Develop performance and functional simulation models
Develop performance and functional testplan and tests to validate new GPU architectural and features
Test and debug on simulators, RTL and real silicon

Skills

Key technologies and capabilities for this role

C++Computer ArchitectureGPU PipelinePerformance ModelingFunctional ModelingSimulation ModelsRTLProfilingISAMicroprocessor DesignShader Unit DesignTrace-driven SimulationExecution-driven Simulation

Questions & Answers

Common questions about this position

What education level is required for this GPU C++ Modeling Engineer role?

A BSEE, BSCSE, or equivalent is required, with MS or PhD being a plus.

What are the key skills needed for this position?

Candidates need in-depth knowledge of computer architecture, good understanding of modern ISA and microprocessor techniques, understanding of GPU concepts and pipeline for graphics and parallel compute, and good mastery of C++ language.

Is this a remote position or does it require working in an office?

This information is not specified in the job description.

What is the compensation or salary for this role?

This information is not specified in the job description.

How can I stand out as a candidate for this job?

Candidates with GPU shader unit design, microprocessor design, and CPU/GPU performance analysis experience are preferred, along with being creative and autonomous.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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