Global Head of AI Compute Infrastructure

UMELIFE (SINGAPORE) PTE. LTD.; Singapore; On-site; SGD 250,000 - 400,000; Full time

Job summary

UMELIFE (SINGAPORE) PTE. LTD. seeks a strategic leader to build and scale its global AI compute infrastructure, spanning Singapore, Hong Kong, China and beyond.

You will define architecture for large-scale GPU clusters, lead procurement, data centre operations and cross-functional collaboration with AI R&D, engineering and finance to align compute capacity with business goals. The role requires 10+ years in AI infrastructure, cloud or HPC, strong leadership, and a track record delivering complex

Qualifications

• Bachelor’s degree or above in CS/Engineering or related field.
• 10+ years in AI infrastructure, cloud computing, data centres, HPC or related fields.
• Proven large-scale GPU cluster deployment experience.
• Leadership and stakeholder management skills.

Responsibilities

• Define and execute the Company’s global AI compute and GPU infrastructure strategy.
• Lead planning, deployment and expansion of large-scale GPU training/inference clusters and data centre infrastructure.
• Drive GPU procurement, supplier management, capacity planning and cost optimisation.
• Establish infrastructure operations, resource scheduling, monitoring, SLA and reliability frameworks.
• Lead AI infrastructure expansion across regions including Singapore, Hong Kong, China and other markets.
• Collaborate with AI R&D, engineering, product, finance and business teams to align compute capacity with business needs.
• Lead and develop AI infrastructure teams and manage technology/data centre partners.
• Evaluate opportunities to commercialise excess GPU capacity and external compute services.
• Lead major initiatives from 0-to-1 through deployment and operations.

Skills

Leadership

Project management

Stakeholder management

Infrastructure planning

GPU infrastructure

Cloud computing

Cost optimisation

Vendor management

Data centre operations

ai infrastructure knowledge

Education

Bachelor's degree in Computer Science or related field

Tools

Kubernetes

GPU compute platforms

Cloud platforms

Job description

AbouttheCompany

WearearapidlygrowingAItechnologycompanywithoperationsacrossChina,HongKongandSingapore,focusedonbuildingnext-generationLLM-poweredAIproductsandintelligentagentplatformsforglobalusers.

TheCompanyiscurrentlyacceleratingthedevelopmentofitsproprietaryLLMandAIAgentinfrastructure,withsignificantinvestmentinGPUcomputingresourcesandAIR&Dcapabilities.Ourtechnologyroadmapcoverslarge-scalemodeltrainingandinference,AIAgents,multimodalAI,intelligentapplicationsandAI-poweredbusinesssolutions.

Asweenterthenextstageofgrowth,wearebuildingaglobalAIcomputeinfrastructurenetworkacrossChina,HongKong,Singaporeandotherinternationalmarkets.ThisincludesthedevelopmentofGPUtrainingandinferenceclusters,datacenterinfrastructure,computeschedulingsystems,GPUsupplychaincapabilitiesandpotentiallythecommercializationofexternalcomputeservices.

WhyThisOpportunity

ThisisastrategicleadershiprolewiththeopportunitytobuildtheCompany’sAIcomputeinfrastructurefromthegroundup.

Job Responsibilities

• Define and execute the Company’s global AI compute and GPU infrastructure strategy.
• Lead the planning, deployment and expansion of large-scale GPU training and inference clusters and data centre infrastructure.
• Drive GPU procurement, supplier management, capacity planning and cost optimisation.
• Establish infrastructure operations, resource scheduling, monitoring, SLA and reliability frameworks.
• Lead AI infrastructure expansion across Singapore, Hong Kong, China and other international markets.
• Work closely with AI R&D, engineering, product, finance and business teams to align compute capacity with business needs.
• Lead and develop AI infrastructure teams and manage strategic technology and data centre partners.
• Evaluate opportunities to commercialise excess GPU capacity and develop external compute services.
• Lead major infrastructure initiatives from 0-to-1 through deployment and large-scale operations.

Job Requirements

• Bachelor’s degree or above in Computer Science, Computer Engineering, IT, Engineering or a related field.
• 10+ years of experience in AI infrastructure, cloud computing, data centres, HPC, GPU infrastructure or related fields.
• Proven experience in large-scale GPU cluster, AI compute or data centre infrastructure deployment.
• Strong knowledge of GPU computing, AI/ML infrastructure, networking, storage and cloud technologies.
• Experience in GPU procurement, capacity planning, vendor management and cost optimisation.
• Experience managing infrastructure projects across multiple countries or regions is preferred.
• Strong leadership, project management and stakeholder management skills.
• Commercial understanding of infrastructure CAPEX/OPEX, utilisation and cost optimisation.
• Experience with LLM training/inference infrastructure, Kubernetes or distributed computing will be an advantage.