Performance Engineer Intern, Deep Learning and HPC - 2026 at NVIDIA

Shanghai, China

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Not SpecifiedCompensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

Technology, AI, High-Performance ComputingIndustries

Requirements

Currently pursuing a bachelor's degree (or higher) in Computer Science, Electrical Engineering, or a related field
Experienced in programming and debugging with scripting languages such as Python or Unix shell
Strong data analysis skills and the ability to summarize findings in a written report
Hands-on experience with Linux based systems
Familiarity using a container platform such as Docker or Singularity
Experience with compiling and running software from source code
Good English verbal and written skills to improve collaboration with coworkers
Fast and self-learning capabilities

Responsibilities

Benchmark, profile, and analyze the performance of AI workloads specifically tailored for large-scale LLM training and inference, as well as High-Performance Computing (HPC) on NVIDIA supercomputers and distributed systems
Aggregate and produce written reports with the testing data for internal sales, marketing, SW, and HW teams
Develop Python scripts to automate the testing of various applications
Collaborate with internal teams to debug and improve performance issues
Assist with the development of tools and processes that improve our ability to perform automated testing
Setup and configure systems with appropriate hardware and software to run benchmarks

Skills

Key technologies and capabilities for this role

BenchmarkingProfilingPerformance AnalysisAI WorkloadsLLM TrainingLLM InferenceHPCPythonAutomationDistributed SystemsGPUSupercomputers

Questions & Answers

Common questions about this position

What education is required for the Performance Engineer Intern position?

Candidates must be currently pursuing a bachelor's degree (or higher) in Computer Science, Electrical Engineering, or a related field.

What are the key skills needed for this internship?

Required skills include experience in programming and debugging with Python or Unix shell, strong data analysis skills, hands-on experience with Linux systems, familiarity with Docker or Singularity, and good English communication skills.

Is this a remote position or does it require on-site work?

This information is not specified in the job description.

What is the compensation or salary for this intern role?

This information is not specified in the job description.

What experience will make me stand out for this role?

Ways to stand out include experience with CI/CD pipelines and DevOps practices, familiarity with Kubernetes or SLURM, curiosity about GPUs and performance benchmarking, knowledge of ML/DL frameworks like TensorFlow or PyTorch, and a background in system-level problem solving.

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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