Senior Deep Learning Software Engineer, FlashInfer at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, TechnologyIndustries

Requirements

Masters degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); PhD preferred
6+ years (academic/industry) experience with ML/DL systems development (preferable)
Strong experience in developing or using deep learning frameworks (e.g., PyTorch, JAX, TensorFlow, ONNX, etc.) and ideally inference engines and runtimes such as vLLM, SGLang, and MLC
Strong Python and C/C++ programming skills

Responsibilities

Innovating and developing new AI systems technologies for efficient inference
Designing, implementing, and optimizing kernels for high impact AI workloads
Designing and implementing extensible abstractions for LLM serving engines
Building efficient just-in-time domain specific compilers and runtimes
Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries, kernels, and GPU arch teams
Contributing to open source communities like FlashInfer, vLLM, and SGLang

Skills

Key technologies and capabilities for this role

Deep LearningGPU KernelsAttention KernelsLLM InferenceKernel Code GeneratorsJIT CompilersAI SystemsFlashInfervLLMSGLang

Questions & Answers

Common questions about this position

What is the base salary range for this position?

The base salary range is 184,000 USD - 287,000 USD, determined based on location, experience, and pay of employees in similar positions.

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

This information is not specified in the job description.

What skills and experience are required for this role?

A Master's degree in Computer Science, Electrical Engineering, or related field (PhD preferred), 6+ years of ML/DL systems development experience, strong experience with deep learning frameworks like PyTorch, JAX, TensorFlow, ONNX, and inference engines like vLLM, SGLang, MLC, plus strong Python and C/C++ programming skills are required.

What is the company culture like at NVIDIA?

NVIDIA offers a diverse, supportive environment where everyone is inspired to do their best work, fueled by innovation and great technology.

What makes a candidate stand out for this position?

Candidates stand out with background in domain specific compilers and libraries for LLM inference (e.g. FlashInfer, Flash Attention), expertise in inference engines like vLLM and SGLang, machine learning compilers (e.g. Apache TVM, MLIR), strong GPU kernel development with CUDA C/C++, cuTile, Triton, and open source project ownership or contributions.

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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