Lead Systems Architect

5 hours ago

Singapore ENTROPICA LABS PTE. LTD. Full time

An overview of this role

This role focuses on designing and specifying the orchestration layer for large-scale, fault-tolerant quantum computers. You will help define how active quantum error correction (QEC) cycles, decoders, and control systems integrate into a coherent architecture that connects hardware, software, and HPC resources.

The role involves analysing Pauli frame propagation, designing I/O interfaces for syndrome decoders, implementing active QEC cycles on hardware testbeds, and evaluating FPGA-based control systems for performance improvements. You will also bring together the quantum node level (QPU, CPU, decoder) with higher-level orchestration across hybrid quantum–classical clusters. Success requires a strong physics background, systems-level thinking, and the ability to work with both quantum software and hardware.

What You will contribute

  • Define orchestration requirements for active QEC in FTQC systems.
  • Model Pauli frame propagation and design syndrome decoding interfaces to enable real-time active QEC.
  • Design and specify I/O interfaces between syndrome decoders and orchestration software.
  • Test and validate active QEC cycles on real quantum hardware.
  • Analyse FPGA-based control systems to identify and implement performance improvements.
  • Define integration strategies for combining HPC and classical orchestration with quantum node-level resource management.
  • Collaborate with hardware teams, control engineers, and software developers to ensure architectural coherence.
  • Contribute to technical documentation, architecture blueprints, and system specifications.

Job Requirements

  • Strong understanding of quantum error correction principles and quantum system dynamics.
  • Experience with modelling quantum systems or control processes.
  • Experience with FPGA programming or low-level control systems is a plus.
  • Familiarity with quantum compilers, decoders, and orchestration frameworks.
  • Proficiency in Python; additional experience in hardware description languages (VHDL, Verilog) is advantageous.
  • Comfort working across software and hardware teams to bridge theory and implementation.
  • Strong communication and documentation skills.
  • PhD or Master's in Physics, Systems Engineering, or related technical discipline

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