Senior Software Engineer, MathDx – cuBLASDx and cuSolverDx at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

High-Performance Computing, Artificial Intelligence, TechnologyIndustries

Requirements

PhD or MSc degree in Computer Science, Applied Math, or a related science or engineering field is preferred (or equivalent experience)
3+ years of experience designing and developing software for high-performance computing and/or AI applications
Advanced C++ skills, including modern design paradigms (e.g., template meta-programming, RAII)
Parallel programming experience with CUDA or OpenCL
Strong collaboration, communication, and documentation habits

Responsibilities

Design modern, flexible, and easy to use APIs for math libraries and lead design reviews with all collaborators
Work closely with internal (e.g., engineering, Product Management) and external partners such as researchers to understand their use cases and requirements
Become a domain expert by continuously surveying current trends in software systems

Skills

Key technologies and capabilities for this role

C++CUDAOpenCLPythonNumPyJAXMLIRtemplate meta-programmingRAIIHPC

Questions & Answers

Common questions about this position

What compensation and benefits does NVIDIA offer for this role?

NVIDIA offers competitive salaries and a generous benefits package.

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

This information is not specified in the job description.

What are the required skills for this Senior Software Engineer position?

Candidates need a PhD or MSc in Computer Science, Applied Math, or related field (or equivalent), 3+ years of experience in HPC/AI software, advanced C++ skills including modern paradigms like template meta-programming and RAII, parallel programming with CUDA or OpenCL, and strong collaboration, communication, and documentation habits.

What is the company culture like at NVIDIA for this team?

The team consists of forward-thinking and hardworking people in exclusive engineering teams that are rapidly growing due to unprecedented growth.

What experience will make me stand out as a candidate?

Experience with graph compilers/JIT like XLA, LLVM, MLIR; Python and automation tools like cmake, CI/CD; CCCL, OpenMP, OpenACC, MPI; numerical methods like FFT and linear algebra; or scientific/deep learning libraries like PyTorch, JAX, MKL will help you stand out.

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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