AI Computing Software Development Engineer, TensorRT-LLM at NVIDIA

Taipei, Taiwan

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Not SpecifiedCompensation

Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

Master or higher degree in Computer Engineering, Computer Science, Applied Mathematics or related computing focused degree (or equivalent experience)
3+ years of relevant software development experience
Excellent Python programming skills, software design, and software engineering skills
Awareness of the latest developments in LLM architectures and LLM inference techniques
Experience working with deep learning frameworks like PyTorch and HuggingFace
Proactive and able to work without supervision
Excellent written and oral communication skills in English

Responsibilities

Craft and develop robust inference software that can be scaled to multiple platforms for functionality and performance
Performance analysis, optimization, and tuning for Large Language Models (LLMs)
Closely follow academic developments in the field of artificial intelligence and feature update TensorRT-LLM
Provide feedback into the architecture and hardware design and development
Collaborate across the company to guide the direction of deep learning inference, working with software, research and product teams
Publish key results in scientific conferences

Skills

Key technologies and capabilities for this role

PythonPyTorchHuggingFaceTensorRT-LLMvLLMSGLangllama.cppMLC-LLMLLM inferencePerformance optimizationDeep Learning FrameworksSoftware Engineering

Questions & Answers

Common questions about this position

What education and experience are required for this role?

A Master or higher degree in Computer Engineering, Computer Science, Applied Mathematics or related field (or equivalent experience) is required, along with 3+ years of relevant software development experience.

What key skills are needed for the Software Development Engineer position?

Excellent Python programming skills, software design, and software engineering skills are required, plus awareness of LLM architectures and inference techniques, and experience with deep learning frameworks like PyTorch and HuggingFace.

What is the compensation like at NVIDIA for this role?

NVIDIA offers competitive salaries and a generous benefits package.

What is the work arrangement or location policy for this position?

This information is not specified in the job description.

What makes a candidate stand out for this TensorRT-LLM role?

Prior experience with LLM inference frameworks like TensorRT-LLM or vLLM, excellent C/C++ skills, GPU programming experience with CUDA or OpenCL, and knowledge of CPU/GPU architecture 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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