Firmus Technologies
51 - 200 employees
🤖 Artificial Intelligence
🔧 Hardware
⚡ Energy
🔥 Funding within the last year
💰 $220.2M Private equity on 2025-10
Artificial Intelligence • Hardware • Energy
<Firmus Technologies> is an AI cloud infrastructure company that builds and operates GPU-powered, scalable, energy-efficient 'AI Factories'—modular, high-density platforms designed for training and serving large machine learning models. They provide cloud compute (GPU clusters and on-demand/bare-metal instances), S3-compatible storage, and platform services aimed at running experiments, training models, and deploying inference at scale, with a strong emphasis on engineering-driven design, sustainability, and regional/sovereign deployments across Asia-Pacific.
Senior AI Infrastructure Engineer – Virtualisation
🕒 March 18
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Firmus Technologies
51 - 200 employees
🤖 Artificial Intelligence
🔧 Hardware
⚡ Energy
🔥 Funding within the last year
💰 $220.2M Private equity on 2025-10
Artificial Intelligence • Hardware • Energy
<Firmus Technologies> is an AI cloud infrastructure company that builds and operates GPU-powered, scalable, energy-efficient 'AI Factories'—modular, high-density platforms designed for training and serving large machine learning models. They provide cloud compute (GPU clusters and on-demand/bare-metal instances), S3-compatible storage, and platform services aimed at running experiments, training models, and deploying inference at scale, with a strong emphasis on engineering-driven design, sustainability, and regional/sovereign deployments across Asia-Pacific.
📋 Description
• Design and implement a highly scalable, multi-tenant control plane that supports Firmus’ growing AI and infrastructure needs • Contribute to the development of exabyte-scale, S3-compatible object storage, distributed file systems, and high-performance filesystems • Work with bare-metal provisioning tools such as Base Command Manager, Warewulf, Ironic, MaaS, and similar platforms • Apply a deep understanding of operating systems, computer networks, software-defined storage, and high-performance applications • Work with technologies including RDMA, GPU Direct Storage, RoCE, InfiniBand, DPDK, Ceph, Weka, DAOS, and others • Collaborate with operations teams to monitor, analyse, and optimise internal clusters and storage platforms • Document architecture designs, operational procedures, and performance results • Collaborate with L2 SRE engineers, site operations, and networking teams to ensure platform reliability, reproducibility, and performance • Contribute to continuous improvement in cluster validation, CI/CD automation, and provisioning and testing frameworks • Apply knowledge of Kubernetes and composable storage clusters • Contribute to the development of custom Kubernetes operators and intelligent orchestration frameworks to optimise AI workload performance for large-scale GPU cluster commissioning
🎯 Requirements
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field • 6–10 years of experience in infrastructure engineering and/or storage engineering • Hands-on experience with bare-metal provisioning • Ability to operate software-defined storage platforms such as Ceph, Weka, Vast Data, DAOS, or Lustre • Solid understanding of cloud-native infrastructure, Kubernetes, and scalable system architectures • Strong debugging and problem-solving skills in distributed, high-performance environments • Practical Linux systems engineering experience (kernel, cgroups, system services, networking, drivers) • Strong automation mindset using tools such as Ansible, Helm, Terraform/OpenTofu, or equivalent • Understanding of firmware, BIOS, BMC/IPMI/Redfish, and low-level system tuning • Proficiency in one or more programming languages such as Go, Bash, Rust, or Python • Excellent documentation skills with strong attention to detail • Experience participating in an on-call rotation supporting production services • Proactive self-starter with a drive for continuous technical improvement.
🏖️ Benefits
• Professional development opportunities • Flexible working hours
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