Linux Systems Engineer - HPC & Hybrid Cloud

Qualcomm; Ciudad de México; Presencial; MXN 600.000 - 900.000; Jornada completa

Descripción de la vacante

Qualcomm seeks a Senior Linux Systems Engineer to manage health, performance, and scalability of massive-scale compute environments powering EDA workloads. You will administer HPC servers on-prem and in the cloud, supporting a Hybrid Cloud strategy and optimizing cost and performance.

You will work with RHEL, Rocky, Ubuntu, and SLES, implement automation, and architect cloud-bursting to scale into public clouds while maintaining parity and observability for large-scale workloads.

Formación

• Bachelor's degree in CS/IS/Engineering or related STEM field.
• 3+ years of direct Linux system administration experience.
• Experience deploying Linux workloads in AWS, Azure, or GCP.
• 5+ years IT-related work experience with or without a Bachelor’s degree.

Responsabilidades

• Provide expert-level administration for RHEL, Rocky Linux, Ubuntu, and SLES.
• Unify infrastructure parity between on-prem and cloud environments.
• Develop script-based automations to capture knowledge and automate workflows.
• Architect and maintain cloud bursting for dynamic scaling of HPC workloads.
• Optimize cloud instance selection for memory- or compute-heavy EDA workloads.
• Implement cost-governance strategies for cloud compute.
• Use observability tools to monitor workloads and identify bottlenecks.
• Interact with HPC job schedulers (Slurm, PBS, LSF) for high throughput.

Educación

Bachelor's degree

Herramientas

Terraform

AWS ParallelCluster

Azure CycleCloud

NetApp Lustre

Descripción del empleo

Qualcomm seeks a Senior Linux Systems Engineer to manage health, performance, and scalability of massive-scale compute environments powering EDA workloads. You will administer HPC servers on-prem and in the cloud, supporting a Hybrid Cloud strategy and optimizing cost and performance.

You will work with RHEL, Rocky, Ubuntu, and SLES, implement automation, and architect cloud-bursting to scale into public clouds while maintaining parity and observability for large-scale workloads.