Nvidia Software Engineer - NIM Production Automation 

Vietnam, Thái Nguyên Province, Thái Nguyên 

941574107

You will work alongside experienced engineers to develop, test, and maintain components that ensure the efficient production and deployment of AI models at scale. This is a fantastic opportunity to gain hands-on experience with cloud-native technologies, large-scale distributed systems, and the AI development lifecycle on thousands of GPUs.

What you'll be doing:

• Develop and deploy containerized applications and microservices (e.g., in Python, Go) supporting NIM production and automation, with guidance from senior engineers.

• Contribute to building and optimizing containerized inference execution for various AI applications.

• Assist in ensuring the performance and scalability of NIMs and automation tools through testing, monitoring, and analysis.

• Contribute to the implementation and maintenance of CI/CD pipelines for automated testing and deployment processes.

• Utilize container technologies (Docker) and orchestration platforms (Kubernetes) in development and deployment tasks.

• Support the enhancement of services for cloud environments, applying Infrastructure as Code (IaC) practices (e.g., Terraform, Ansible).

• Collaborate with team members to troubleshoot issues, debug code, and improve existing systems.

• Actively participate in team discussions, code reviews, and contribute to a collaborative engineering culture.

What we need to see:

• A Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field (or equivalent experience).

• 0-2 years of software development experience (internships and significant academic projects count!).

• Solid programming fundamentals, with experience in languages like Python or Go.

• Familiarity with basic software development concepts (e.g., version control with Git, testing).

• An understanding of or strong interest in learning about containerization (Docker) and orchestration (Kubernetes).

• Interest in cloud technologies and distributed systems.

• A passion for problem-solving and eagerness to learn new technologies.

• Good communication and collaboration skills.

• Enthusiasm for AI/ML technologies.

Ways to stand out from the crowd:

• Prior internship experience in software development, cloud computing, or infrastructure.

• Personal projects demonstrating experience with Python/Go, Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure).

• Exposure to CI/CD tools (e.g., GitLab CI).

• Basic understanding of microservice architectures.

• Contributions to open-source projects.