Deep Learning Performance Architect - New College Grad 2026 at NVIDIA

Shanghai, China

Apply Now

Not SpecifiedCompensation

Entry Level & New GradExperience Level

Full TimeJob Type

UnknownVisa

Technology, AIIndustries

Requirements

BS or higher degree in a relevant technical field (CS, EE, CE, Math, etc.)
Strong programming skills in Python, C, C++
Strong background in computer architecture
Experience with performance modeling, architecture simulation, profiling, and analysis
Prior experience with LLM or generative AI algorithms

Responsibilities

Analyze state of the art DL networks (LLM etc.), identify and prototype performance opportunities to influence SW and Architecture team for NVIDIA's current and next gen inference products
Develop analytical models for the state of the art deep learning networks and algorithm to innovate processor and system architectures design for performance and efficiency
Specify hardware/software configurations and metrics to analyze performance, power, and accuracy in existing and future uni-processor and multiprocessor configurations
Collaborate across the company to guide the direction of next-gen deep learning HW/SW by working with architecture, software, and product teams

Skills

Key technologies and capabilities for this role

PythonCC++Computer ArchitecturePerformance ModelingArchitecture SimulationProfilingLLMGenerative AICUDAOpenCLPyTorchTensorRT-LLMvLLMTritonMLIRTVMXLA

Questions & Answers

Common questions about this position

What degree is required for this Deep Learning Performance Architect role?

A BS or higher degree in a relevant technical field such as CS, EE, CE, Math, etc. is required.

What programming skills are needed for this position?

Strong programming skills in Python, C, and C++ are required.

What experience is essential for this role?

Candidates need a strong background in computer architecture, experience with performance modeling, architecture simulation, profiling, and analysis, and prior experience with LLM or generative AI algorithms.

What skills will help me stand out for this job?

To stand out, have experience in GPU Computing and parallel programming models such as CUDA and OpenCL, architecture or workload analysis on deep learning accelerators, deep neural network training/inference/optimization in frameworks like Pytorch or TensorRT-LLM, and open-source AI compilers like OpenAI Triton or MLIR.

What is the work environment like at NVIDIA for this role?

NVIDIA fosters a diverse work environment and is committed to being an equal opportunity employer, with collaboration across architecture, software, and product teams in a dynamic technology-focused company.

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.

Land your dream remote job 3x faster with AI

Try Jobo Free