System Software Engineer, AI Data Platform
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System Software Engineer, AI Data Platform
Location
Vietnam, Ho Chi Minh City • Vietnam, Hanoi
Experience
Mid
Posted
Jul 10, 2026
Apply by
August 9, 2026
Applicants
0
Early applicantFull-timeWork from Office
Job Description
Our team is building the foundational infrastructure that powers NVIDIA’s cutting-edge innovations in AI and high-performance computing. We are looking for a System Software Engineer to help design, build, and improve scalable and reliable automation systems that support the development, validation, and deployment of our core software across cloud and on-premises environments. This role offers the opportunity to work on large-scale systems that ensure the performance, reliability, and efficiency of AI and compute workloads used globally—from data centers to specialized hardware platforms.
**What You’ll Be Doing:**
- Develop and maintain infrastructure and tools that automate software build, test, and deployment workflows.
- Build and improve performance measurement and benchmarking systems for large-scale software and hardware platforms.
- Collaborate with engineering teams to understand requirements and deliver reliable, scalable solutions.
- Analyze system performance and logs to identify issues and contribute to continuous improvements.
- Participate in design discussions and help improve platform automation and engineering efficiency.
**What We Need To See:**
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related field, or equivalent experience.
- At least 2+ years of software engineering experience in infrastructure, backend systems, distributed systems, or automation.
- Strong programming skills in at least one of: C++, Python, Go, or similar languages.
- Experience working with software systems, automation frameworks, or CI/CD pipelines.
- Strong problem-solving and debugging skills.
- Good communication skills and ability to work effectively in a team.
**Ways To Stand Out From The Crowd:**
- Exposure to AI/ML systems or data-intensive workloads.
- Experience with cloud or on-prem infrastructure environments.
- Familiarity with container technologies such as Docker and Kubernetes.
- Experience with performance analysis or profiling tools.
- Interest in building scalable systems and improving engineering efficiency.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family[www.nvidiabenefits.com](https://www.linkedin.com/safety/go/?url=http%3A%2F%2Fwww%2Envidiabenefits%2Ecom&urlhash=GnQ2&mt=wOHt8OVGAuwO7uonawkRvR5uvNK5x_V2cfgbWEkvkbuq2Y-VXrLyZCAmK8Le3EbUssMB-aQkviFSjZs37lbkZg7q8r4&isSdui=true)
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Key Responsibilities
- Develop and maintain infrastructure and tools to automate software build, test, and deployment workflows.
- Build and improve performance measurement and benchmarking systems for large-scale software and hardware platforms.
- Collaborate with engineering teams to understand requirements and deliver reliable, scalable solutions.
- Analyze system performance and logs to identify issues and contribute to continuous improvements.
- Participate in design discussions and help improve platform automation and engineering efficiency.
Requirements
- Bachelor's or Master's degree in Computer Science
- Computer Engineering
- or related field
- or equivalent experience
Skills Required
C++PythonGoInfrastructureBackend systemsDistributed systemsAutomationCI/CD pipelinesProblem-solvingDebuggingCommunicationTeamworkAI/ML systemsData-intensive workloadsCloud infrastructureOn-prem infrastructureDockerKubernetesPerformance analysis toolsProfiling tools
Benefits
- Competitive salaries
- Comprehensive benefits package
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