Cluster Administration Engineer (AI)

Location: On-site in Singapore

Annual salary: S$200,000–S$400,000 plus equity

Company

hirify.global develops and operates infrastructure for vLLM, an AI inference engine, with a focus on making model inference faster and more cost-effective.

What you will do

• Own the health, availability, observability, and usability of high-performance GPU and HPC clusters.
• Manage GPU availability, monitoring, alerting, scheduling, access, diagnostics, and incident response.
• Operate GPU servers, troubleshoot node failures, memory errors, driver issues, scheduler problems, and hardware faults.
• Standardize provisioning, operations, debugging, and scaling across neo-cloud and dedicated compute providers.
• Automate operational workflows and improve cluster utilization while reducing idle or unavailable GPU capacity.
• Work with engineering leadership and infrastructure owners to keep compute systems productive for engineering teams.

Requirements

• Bachelor’s degree or equivalent experience in computer science, engineering, systems administration, or a related field.
• Hands-on experience administering large compute, HPC, research, supercomputing, or production GPU clusters.
• Strong Linux systems administration skills, including networking, processes, storage, package management, shell scripting, logs, access control, and debugging.
• Experience with cluster scheduling and resource allocation using SLURM, Kubernetes, or equivalent tools.
• Ability to own urgent infrastructure incidents end to end when compute issues block engineering teams.
• Experience with Bash, Python, Ansible, Terraform, Helm, or similar automation tools.

Nice to have

• Experience with GPU compute providers such as Lambda, CoreWeave, Crusoe, Nebius, Together, Fireworks, or RunPod.
• Knowledge of InfiniBand, RoCE, NVLink, NVSwitch, RDMA, NCCL, or equivalent high-performance GPU networking systems.
• Experience with NFS, Lustre, Ceph, distributed filesystems, or other high-throughput storage systems.
• Background in research computing, scientific computing, ML infrastructure, SRE, platform engineering, or infrastructure operations.
• Experience operating Kubernetes for ML or GPU workloads and standardizing infrastructure across multiple providers.

Culture & Benefits

• Visa sponsorship is available on a case-by-case basis.
• Medical, dental, and vision coverage.
• Equity in addition to the annual salary.
• Infrastructure supports engineering and research workloads around the clock.