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Customer Engineer, High Performance Computing, Google Cloud

Google· Google Cloud
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SingaporeFull-timePosted 3d ago

About the role

Specialist Customer Engineers seek to accelerate Google Cloud customer success by providing domain-specific technical expertise, while responsibly influencing products and solutions. In this role you partner with technical Sales teams as a subject matter expert in High Performance Computing (HPC) to differentiate Google Cloud to customers, develop cloud solutions, engage in proofs of concepts, and troubleshoot technical questions and roadblocks.

Responsibilities

  • Drive pre-sales technical strategy and build go-to-market solutions with customers and data center hosting partners to accelerate business cycles, resolve technical objections, and land large-scale Google Cloud TPU agreements and deployments across APAC.
  • Serve as a trusted technical advisor on end-to-end architecture and integration strategies across the TPU software stack and customer or partner environments (fleet management systems, job schedulers, IaaS operations tooling, ancillary storage/compute, and data center networking/WAN).
  • Guide customers and hosting partners through technical qualification, pod layout design, system turn-up, and operational readiness—covering slice lifecycle management, OS and firmware upgrades, telemetry integration, and hardware maintenance workflows.
  • Conduct workload performance profiling, workload migration, and optimization of large-scale training and inference models and data pipelines specifically for Google Cloud TPU hardware topologies (e.g., 3D Torus over Inter-Chip Interconnect and Optical Circuit Switches).

Qualifications

  • Bachelor's degree or equivalent practical experience.
  • 6 years of experience with cloud-native or high-performance computing (HPC) infrastructure architecture in a customer-facing pre-sales, solutions architecture, or deployment engineering role.
  • Experience developing, deploying, and orchestrating distributed AI/ML workloads using modern frameworks (e.g., PyTorch, JAX, vLLM, or SGLang) and job schedulers (e.g., Kubernetes or Slurm) on AI accelerator hardware.
  • Experience with Linux host software, cluster control planes, and data center infrastructure integration (compute, high-speed networking, and storage).

Skills

Required:Cloud-native / HPC infrastructureAI/ML workloads deploymentFrameworks (PyTorch, JAX, vLLM, SGLang)Job schedulers (Kubernetes, Slurm)Linux and data center infra
Nice to have:System design & pre-sales collaborationMandarin communication
Last updated Oct 23, 2026. Interested? Apply on the company site.

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