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Company Overview
This organization is a leading provider of high-performance computing (HPC) solutions and cloud infrastructure services. It specializes in building resilient, scalable, and secure computing platforms for enterprise and research applications. The company fosters a culture of technical excellence, innovation, and collaboration, providing teams with cutting-edge tools and resources to drive performance and efficiency in HPC environments.
Job Title: Staff Platform Engineer – High Performance Computing Platform Management Location: Singapore, Singapore Employment Type: Full-time, On-site Department: Cloud Infrastructure and Services – Big Data Platform
Job Description Responsibilities
• Lead a team to deliver resilient, scalable, and secure HPC platforms, including compute nodes, storage systems, networks, and job scheduling systems.
• Design, implement, and manage HPC infrastructure platforms to meet organizational needs.
• Develop storage solutions for HPC workloads to ensure efficient data storage and retrieval.
• Design and implement high-performance networking solutions, including InfiniBand, Ethernet, and other interconnects.
• Plan and manage HPC resource capacity, including forecasting, procurement, and deployment of new hardware and software.
• Manage HPC clusters, including optimization, monitoring, troubleshooting, and job scheduling/resource allocation.
• Ensure security and compliance of the HPC infrastructure, including access controls, patches, and regular security audits.
• Collaborate with stakeholders such as data scientists and developers to optimize application performance and provide technical support on HPC usage.
Qualifications
• Degree in Computer Science, Computer Engineering, or a related field.
• 8+ years of experience managing HPC systems, including Linux, Unix, or equivalent operating systems.
• Strong understanding of HPC architectures, including clusters, grids, and cloud environments.
• Experience with HPC job scheduling systems such as Slurm, Torque, or LSF.
• Expertise in storage systems, including SAN, NAS, and object storage.
• Experience with high-performance networking, including InfiniBand and Ethernet interconnects.
• Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud.
• Proficiency in scripting languages like Python, Perl, or Bash.
• Experience with containerization tools (Docker, Kubernetes) and complementary technologies including Knative, Run:AI, Grafana, Prometheus, Kyverno, ArgoCD, Rancher, NVIDIA BCM, and NVIDIA Superpod architecture.
• Proven experience in leading engineering teams.
Nice to Have
• Certifications in NVIDIA AI Infrastructure and Operations or Certified Kubernetes Administrator.
• Experience with machine learning or deep learning frameworks such as TensorFlow or PyTorch.
• Familiarity with agile development methodologies and version control systems like Git.
Disclaimer
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