Tuyển dụng AI Infrastructure Engineer GPU & Colocation tại Hồ Chí Minh

We are building our own GPU infrastructure to run AI models, support AI-driven software development, and power AI capabilities in our software products. We are looking for a hands-on engineer to build this infrastructure in a colocation data centre and take responsibility for its ongoing operation.

You will turn workload requirements into a practical infrastructure setup—from selecting servers and coordinating installation to configuring Linux, deploying model-serving environments, and keeping systems secure and reliable.

Your Responsibilities

Plan and Build the Infrastructure

• Translate AI workload requirements into GPU, compute, storage, and networking configurations.

• Evaluate hardware compatibility, supplier proposals, and costs.

• Coordinate procurement, delivery, installation, and commissioning.

• Confirm rack space, power, cooling, connectivity, and access requirements with the colocation provider.

• Install and configure servers, networking equipment, cabling, and remote management.

• Maintain infrastructure documentation and asset inventories.

Configure GPU and AI Systems

• Configure and maintain Linux servers, GPU drivers, CUDA environments, and container runtimes.

• Deploy and maintain model-serving infrastructure in collaboration with the AI and engineering teams.

• Diagnose GPU, memory, storage, and network performance issues.

• Benchmark workloads and improve resource utilisation.

• Automate deployment and configuration to make environments reproducible.

Manage Networking and Security

• Configure network segmentation, firewalls, VPNs, and secure administrative access.

• Implement access controls, credential management, system hardening, and patching.

• Separate workloads and environments according to product and security requirements.

• Troubleshoot connectivity issues with infrastructure providers.

Own Reliability and Operations

• Establish monitoring and alerting for hardware health, GPU utilisation, capacity, and service availability.

• Implement backup and recovery procedures and test restoration.

• Maintain operational runbooks and troubleshoot infrastructure incidents.

• Coordinate hardware replacements, maintenance windows, and remote-hands support.

• Identify single points of failure and propose practical improvements.

• Establish clear support coverage and escalation procedures with the team.

Manage Capacity and Costs

• Track utilisation, operating costs, and capacity constraints.

• Recommend upgrades based on measured demand and performance.

• Assess trade-offs between owned hardware, rented GPU capacity, and cloud services.

• Plan expansion while avoiding unnecessary complexity and overprovisioning.

What You Bring

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Yêu cầu công việc

What You Bring

• Hands-on experience deploying and operating physical servers in a data centre or colocation environment.

• Strong Linux administration and troubleshooting skills.

• Practical experience with GPU servers, NVIDIA drivers, CUDA, and AI workloads.

• Solid networking knowledge, including switching, routing, VLANs, firewalls, and VPNs.

• Experience with containers, monitoring, backups, and infrastructure automation.

• An understanding of rack power, cooling, hardware compatibility, and remote server management.

• A disciplined approach to security, documentation, maintenance, and recovery.

• The ability to work independently and coordinate with vendors and data centre providers.

• Professional English for technical documentation and collaboration.

• Willingness to perform on-site installation and maintenance when required.

Useful Additional Experience

• Operating AI inference and model-serving systems.

• Managing multi-GPU workloads and high-speed networking.

• Using infrastructure-as-code and configuration-management tools.

• Supporting environments with workload isolation and availability requirements.

How You Will Work

• You will own the implementation and reliable operation of our AI infrastructure, working closely with the AI and software engineering teams to align infrastructure with application and model requirements.

• This is a hands-on role covering both the initial build and ongoing operations, with direct involvement in model deployment, performance optimisation, capacity planning, and infrastructure decisions.

What Success Looks Like

• Infrastructure meets agreed workload, security, and operational requirements.

• AI workloads run reliably with measurable performance and utilisation.

• Monitoring, tested recovery procedures, and operational documentation are in place.

• Infrastructure costs are transparent and expansion decisions are based on evidence.

• Incidents are resolved effectively, with clear coordination across suppliers and service providers.

Quyền lợi

• Thưởng: Theo quy định công ty