Solution Architect, Generative AI - CSP at NVIDIA

Beijing, China

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

MS or PhD in Electrical Engineering, Computer Science/Engineering, Mathematics, Physics, or a related field (or equivalent experience)
3+ years of work-related experience in AI for natural language processing (NLP) and large language model (LLM)
Knowledge of application areas such as natural language processing and computer vision
Excellent programming skills in some rapid prototyping environments such as Python, C++ and parallel programming (e.g., CUDA) is a plus
Expertise with deep learning frameworks such as PyTorch
Strong written and oral communications skills in English
Ways to stand out
Background in large language model, generative AI, recommender system
Demonstrated experience optimization workloads with GPU technology
Experience with NVIDIA AI and Data Science software and platform

Responsibilities

Assisting field business development in guiding the customer build/extend their GPU infrastructures for AI
Help customers build their large-scale projects, especially Large Language Model (LLM) projects
Engage with customers to perform in-depth analysis and optimization to ensure the best performance on GPU architecture systems. This includes support in optimization of both training and inference pipelines
Partner with Engineering, Product and Sales teams to develop, plan best suitable solutions for customers. Enable development and growth of product features through customer feedback and proof-of-concept evaluations
Build industry expertise and become a contributor in integrating NVIDIA technology into Enterprise Computing architectures

Skills

Key technologies and capabilities for this role

Generative AILarge Language ModelsLLMRecommender SystemsGPU InfrastructureNeural NetworksTraining PipelinesInference PipelinesAI OptimizationGPU Architecture

Questions & Answers

Common questions about this position

What education and experience are required for this Solution Architect role?

A MS or PhD in Electrical Engineering, Computer Science/Engineering, Mathematics, Physics, or a related field (or equivalent experience) is required, along with 3+ years of work-related experience in AI for natural language processing (NLP) and large language model (LLM). Knowledge of application areas such as natural language processing and computer vision is also needed.

What programming skills and frameworks are preferred for this position?

Excellent programming skills in rapid prototyping environments such as Python, C++ and parallel programming (e.g., CUDA) are a plus, along with expertise with deep learning frameworks such as PyTorch.

What is the salary or compensation for this role?

This information is not specified in the job description.

Is this position remote or does it require office work?

This information is not specified in the job description.

What qualities or experience make a candidate stand out for this role?

Candidates stand out with a background in large language model, generative AI, recommender system, demonstrated experience optimizing workloads with GPU technology, and experience with NVIDIA.

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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