Software Engineer, cuDNN - Deep Learning at NVIDIA

Shanghai, China

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Not SpecifiedCompensation

Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

M.S. degree in computer science (or similar) or equivalent experience
2+ years of relevant work or research experience
Strong programming skills in C/C++ development
Work experience with CUDA development
Familiarity with Python
Good understanding of linear algebra
Familiarity with the latest trends in machine learning
Experience designing high level software architecture
Good problem solving skills, including applications of algorithms and data structures
Experience with performance analysis, profiling, and code optimization

Responsibilities

Develop production-quality software that ships as part of NVIDIA's AI software stack, including optimized large language model (LLM) support
Analyze the performance of important workloads, tuning our current software, and proposing improvements for future software
Work with cross-collaborative teams of deep learning software engineers and GPU architects to innovate across applications like generative AI, autonomous driving, computer vision, and recommender systems
Adapt to the constantly evolving AI industry by being agile and excited to contribute across the codebase, including API design, software architecture, performance modeling, testing, and GPU kernel development

Skills

Key technologies and capabilities for this role

C/C++CUDAPythonLinear AlgebraMachine LearningSoftware ArchitectureAlgorithmsData StructuresPerformance OptimizationGPU Programming

Questions & Answers

Common questions about this position

What education and experience are required for this Software Engineer role?

An M.S. degree in computer science or equivalent experience is required, along with 2+ years of relevant work or research experience.

What programming skills are needed for this position?

Strong programming skills in C/C++ development, experience with CUDA development, and familiarity with Python are required.

What are the must-have technical skills beyond programming?

Candidates need a good understanding of linear algebra, familiarity with the latest trends in machine learning, experience designing high-level software architecture, good problem-solving skills with algorithms and data structures, and experience with performance analysis, profiling, and code optimization.

What ways can I stand out as a candidate for this role?

Stand out with GPU programming and optimization expertise like CUDA or OpenCL, practical experience with machine learning especially deep learning, experience with computer architecture and performance models for CPUs/GPUs, and familiarity with MLIR development and compiler optimization.

Is the salary or compensation mentioned for this position?

This information is not specified in the job description.

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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