Senior AI Infrastructure Software Engineer at NVIDIA

Shanghai, China

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, SemiconductorIndustries

Requirements

Master or PhD or equivalent experience in Computer Science or related field, with a minimum of 5 years in large-scale distributed systems or AI infrastructure
Advanced expertise in Python (required), strong experience with JavaScript, and deep knowledge of software engineering principles, OOP/functional programming, and writing high-performance, maintainable code
Demonstrated expertise in crafting scalable microservices, web apps, SQL, and NoSQL databases (especially MongoDB and Redis) in production with containers, Kubernetes, and CI/CD
Solid experience with distributed messaging systems (e.g., Kafka), and integrating event-driven or decoupled architectures into robust enterprise solutions
Practical experience integrating and fine-tuning LLMs or agent frameworks (e.g., LangChain, LangGraph, AutoGen, OpenAI Functions, RAG, vector databases, timely engineering)
Demonstrated end-to-end ownership of engineering solutions, from architecture and development to deployment, integration, and ongoing operations/support
Excellent communication skills and a collaborative, proactive approach

Responsibilities

Design, develop, and improve scalable infrastructure to support the next generation of AI applications, including copilots and agentic tools
Drive improvements in architecture, performance, and reliability, enabling teams to bring to bear LLMs and advanced agent frameworks at scale
Collaborate across hardware, software, and research teams, mentoring and supporting peers while encouraging best engineering practices and a culture of technical excellence
Stay informed of the latest advancements in AI infrastructure and contribute to continuous innovation across the organization

Skills

Key technologies and capabilities for this role

PythonJavaScriptDistributed SystemsAI InfrastructureLLMsAgent FrameworksOOPScalable Infrastructure

Questions & Answers

Common questions about this position

What education and experience are required for this role?

A Master or PhD or equivalent experience in Computer Science or related field is required, along with a minimum of 5 years in large-scale distributed systems or AI infrastructure.

What programming languages and technical skills are needed?

Advanced expertise in Python is required, strong experience with JavaScript, and deep knowledge of software engineering principles including OOP/functional programming, scalable microservices, web apps, SQL/NoSQL databases like MongoDB and Redis, containers, Kubernetes, CI/CD, Kafka, and LLM/agent frameworks like LangChain.

What is the salary or compensation for this position?

This information is not specified in the job description.

Is this role remote or does it require office work?

This information is not specified in the job description.

What does NVIDIA's team culture look like?

The team operates at the intersection of research, engineering, and product development, collaborating closely across hardware, software, and research teams while encouraging best engineering practices, technical excellence, and continuous innovation. NVIDIA brings together innovative and dedicated minds in the industry.

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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