System Engineer

Responsibilities:

1. Manage internal IT infrastructure, ensuring that cloud-native security measures are in place, and the solutions are scalable, maintainable, performance, secure, and meet industry standards/best practices and business needs.
2. Focus on designing, implementing, and maintaining the underlying cloud infrastructure such as virtual machines host, storage, and networking components.
3. Monitor and maintain cloud infrastructure solutions daily, including resource usage, performance metrics, issue resolution, and infrastructure configuration optimization.
4. Involve in project management and maintain the project life cycle, process & deliverables to ensure positive outcomes.
5. Create technical documentation for cloud infrastructure solutions, including SoP, SoW, UAT, etc.
6. Manage change requests such as assessing potential threats and vulnerabilities, security patching, system configuration changes.
7. Provide technical support, administration and guidance on internal IT Infrastructure, for cloud and HPC-related projects.
8. Provide 2nd tier of operational support to ensure customer’s technical issues are resolved.
9. Collaborate with cross-functional teams to support the deployment of machine learning models and HPC workloads.
10. Stay updated with emerging technologies and advancements in cloud computing, containerization, and AI/ML.

Requirements:

• Bachelor’s degree in computer science or any computer-related field.
• Good work attitude and coordination ability, learning ability, good at communicating with people and teamwork.
• Good command in English both speaking and writing.
• Hands-on experience in Linux system administration.
• Experience in the following areas is preferred but not required:

          a. Solid understanding of Linux operating systems and proficient use of Ansible for automation. Familiarity with cloud service providers (e.g., AWS, Azure, Google Cloud) and their services.

           b. Containerization and Orchestration: Hands-on experience with Docker, Kubernetes, and other container management solutions. Ability to design, deploy, and manage containerized applications.

           c. Experience in automate deployment, scaling, and management tasks using Ansible and other tools.

           d. HPC Cluster Management: Experience in managing and optimizing HPC clusters, with a focus on efficiency and performance. Knowledge of cluster management tools and practices.

           e. MLOps: Familiarity with Machine Learning Operations (MLOps) principles and workflows. Experience in integrating ML models into production environments is a plus.

           f. Nvidia AI Enterprise Solutions: Experience with Nvidia AI enterprise solutions, including Base Command Manager, is highly desirable. Understanding of AI/ML frameworks and their deployment on Nvidia platforms.

           g. Comfortable and confident in presenting solutions to both internal and external stakeholders.