System Performance Modeling Engineer/Architect (AI)

Location: Singapore

Company

hirify.global is a technology company focused on Bitcoin mining, ASIC hardware, high-performance computing, and AI cloud infrastructure.

What you will do

• Build and maintain cycle-approximate and analytical full-chip models of tile arrays, NoC, and memory subsystems using C++, SystemC, and Python.
• Perform workload mapping, roofline analysis, bottleneck analysis, and traffic modeling across the tile array and memory hierarchy.
• Evaluate architecture trade-offs involving tile count, local memory, NoC topology and bandwidth, memory channels, and QoS.
• Correlate model predictions against RTL, emulation, FPGA implementations, and later silicon to reduce the modeling-to-reality gap.
• Provide golden-reference hooks for performance and verification sign-off.
• Maintain dashboards and trade-off reports for architecture and program leadership.

Requirements

• 5+ years of experience in performance modeling or architecture for SoCs and accelerators.
• Strong C++ and Python skills, with experience in SystemC or a comparable cycle-approximate modeling framework.
• Strong knowledge of memory hierarchies, bandwidth and latency trade-offs, interconnect and NoC behavior, and roofline analysis.
• Ability to model subsystems and translate quantitative results into architecture decisions.
• Experience working with incomplete specifications and collaborating across architecture, design, and software teams.

Nice to have

• Experience with NoC or interconnect modeling, memory-controller behavior, or 3D-DRAM/HBM bandwidth analysis.
• Exposure to compiler and dataflow co-design for accelerators.
• Experience correlating models against RTL, emulation, FPGA, or silicon results.
• Background in tile-based or dataflow architectures.

Culture & Benefits

• Inclusive environment that values diverse perspectives and backgrounds.
• Startup-oriented, fast-growing environment with opportunities to work on new projects and systems.
• Autonomy, personal accountability, professional growth, and learning opportunities.
• Training, mentoring, welfare benefits, and opportunities to contribute to digital asset and AI infrastructure.