Head of Digital Twin Platform (AI)

Location: Based in Singapore or Australia, with travel to hirify.global AI Factory sites and partner engineering teams as required

Company

hirify.global Technologies develops and operates sustainable AI infrastructure across Asia Pacific, including AI Factories and the hirify.global AI Cloud GPU platform.

What you will do

• Own the architecture and roadmap for AIFactoryX, a simulation, optimisation, and digital twin platform covering physical plant, compute, networking, energy, and commercial models.
• Lead the engineering pipeline from design master and CAD models through CFD, electrical studies, NVIDIA Omniverse, and OpenUSD while keeping models aligned with live designs.
• Define model fidelity, calibration, uncertainty, validation, and evidence standards using commissioning data, AIFactoryOS telemetry, and physics-ML surrogates where appropriate.
• Turn simulation results into design, site-selection, operational, failure-recovery, investment, and incident-analysis decisions, including traceable Bases of Design.
• Own delivery planning, weekly execution, compute and tooling availability, licences, budgets, and the initial proof of the platform on one site and one Hypercube before portfolio expansion.
• Build and lead a multidisciplinary team, establish software quality, reproducibility, data lineage, and security standards, manage NVIDIA, solver, and engineering-partner relationships, and report progress and model confidence to the CTO.

Requirements

• 12–15+ years across systems engineering, simulation or computational engineering, and large-scale software platforms.
• Degree in engineering, physics, applied mathematics, or a closely related discipline.
• Experience leading a team that built production simulation or digital twin platforms used for real engineering, operating, or investment decisions rather than demonstrations.
• Experience designing interfaces and data models for other engineers and a strong systems-engineering foundation in requirements, trade studies, verification, and validation.
• Experience applying systems engineering to complex physical systems such as data centres, power systems, process plants, aerospace, or semiconductors.
• Depth in at least one discipline such as thermal and cooling, electrical engineering, or compute and network modelling, with the ability to learn the others.
• Understanding of model validation and reliability limits, plus comfort reading and reviewing code.

Nice to have

• Experience in AI or HPC infrastructure.
• Experience with NVIDIA Omniverse and DSX.
• Experience with industrial digital twins in high-availability environments.

Culture & Benefits

• Permanent full-time employment.
• Founder-led environment with fast decisions, accessible leadership, and limited bureaucracy.
• Early ownership and direct contribution to long-term, large-scale AI infrastructure outcomes.
• Opportunity to work with founders and specialists in AI infrastructure, energy systems, and next-generation compute.
• Inclusive workplace encouraging applications from candidates of all backgrounds.