Senior SWQA Test Development Engineer - DGX Cloud at NVIDIA

Shanghai, China

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, AI, Cloud ComputingIndustries

Requirements

BS or higher degree or equivalent experience in CS/EE/CE with 5+ years QA experience
Experience using AI tools for QA tasks
Familiarity with AI-powered testing frameworks and platforms that improve process efficiency
Strong understanding of QA methodologies and the ability to integrate AI tools into existing workflows
Proficient in Unix/Linux and shell/python programming skills with a strong understanding of Kubernetes architecture and its components
Experience with containerization technologies
Experience with CI/CD pipelines and tools
Hands-on experience in testing observability solutions (Prometheus, Grafana, ELK Stack, Datadog, etc.) and validating metrics, logs, traces, and alerting workflows
Proven experience in test cases development, tests automation and failure analysis, preferably with Kubernetes or cloud-based services, simulating large clusters and testing various failures (tools like KWOK and chaos monkey, etc.)
Good QA sense, knowledge, and experience in software testing who is an excellent communicator, fluent written and verbal English

Responsibilities

Utilizing AI-powered tools to enhance QA efficiency, including automating test case generation, defect detection, and regression testing
Implementing AI-driven solutions to optimize test coverage and identify high-risk areas in software systems
Collaborating with cross-functional teams to adopt AI tools that improve workflow automation and reduce manual effort
Review product requirements and collaborate with cross-functional teams to define test requirements/strategies
Build test plan, design test case, execute and report test progress, bugs and results to management
Perform Function, Performance, Fault Injection and reliability testing
Automate test cases and assist in the architecture, crafting and implementing of test frameworks
Manage bug lifecycle and co-work with inter-groups to drive for solutions
In-house repro and verify customer issues/fixes
Leveraging AI-powered tools to automate repetitive testing tasks, optimize test coverage, and detect flaky tests

Skills

AI-powered tools

QA automation

test case generation

defect detection

regression testing

test frameworks

QA methodologies

function testing

performance testing

fault injection

reliability testing

bug lifecycle

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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