System Modeling and Simulation Lead (Quantum Systems)

PsiQuantums mission is to build the first useful quantum computers: machines capable of delivering the breakthroughs the field has long promised. Since our founding in 2016 our singular focus has been to build and deploy million-qubit fault-tolerant quantum systems.

Quantum computers harness the laws of quantum mechanics to solve problems that even the most advanced supercomputers or AI systems will never reach. Their impact will span energy pharmaceuticals finance agriculture transportation materials and other foundational industries.

Our architectureand approachisbased on silicon photonics. Byleveragingthe advanced semiconductor manufacturing industry including partners like GlobalFoundries we use the same high-volume processes that already produce billions of chips for telecom and consumer electronics. Photonics offers natural advantages for scale: photonsdontfeel heat are immune to electromagnetic interference and integrate with existing cryogenic cooling and standard fiber-optic infrastructure.

That approach has since been tested at the highest level of scrutiny the U.S. government applies to emerging technology and it has held 2025PsiQuantumclosed a$1 billionfunding round that valued the company at$7 2026 the U.S. Department of Commerce signed a $100 million Letter of Intent under the CHIPS and Science Act followed by a $125 million agreement with DARPA under Stage C of its Quantum Benchmarking InitiativePsiQuantumsmost valuable U.S. government agreement to date. This year we also broke ground on our utility-scale quantum computer in Brisbane Australia and continued building out our Chicago site. Victor Peng our CEO and co-founder Jeremy OBrien now ExecutiveChairman lead a team and board that reflects how seriously the world is taking this build joined this year by Intels Lip-Bu Tan and Atomicos NiklasZennström.

PsiQuantumalso develops the algorithms and software needed to make these systems commercially valuable. Our application software and industry teams work directly with leading Fortune 500 companies includingAirbusLockheedMartin Mercedes-Benz Boehringer Ingelheim and Mitsubishi Chemical to prepare quantum solutions for real-world impact.

Quantum computing is not an extension of classical computing. Itrepresentsa fundamental shift and a path to mastering challenges that cannot besolvedany other way. The potential is enormous and we now havethe fundingthe governmentvalidation andthe sitesunder construction to make it real.

Job Summary:

Were looking for a System Modeling and Simulation Lead to build predictive system-level models of our quantum computer based on photonic electronic and other system descriptions together with measured or specified component performance. The models will translate losses noise timing jitter stability crosstalk false-count rates and related nonidealities into key quantum performance metrics. This role will also create validated subsystem abstractions that conceal unnecessary implementation detail while preserving the behavior and control knobs needed by validation architecture and design teams for predictive analysis and model closure. These capabilities must be delivered through user-friendly well-documented interfaces so teams across the organization can configure run and interpret approved models without needing to understand their internal implementation.

Responsibilities:

• Build predictive system-level quantum performance models
  • Ingest and interpretphotonic electronic and mixed-domain system descriptions component models characterization data and system configuration inputs.
  • Translate component and interface performance - includingloss noise jitter drift and stability crosstalk and false-count rates - into end-to-end predictions of key quantum system metrics.
  • Develop models that supportarchitecture trades requirement allocation performance budgeting and design decisions before full hardware is available.
• Develop coherent reusable system abstractions
  • Createreduced-order or behavioral models that connect logical intent to physical-system behavior and support control calibration and validation workflows while masking lower-level implementation details that are not needed by model users.
  • Define stable model interfaces and expose thenecessary inputs outputs states uncertainties and control knobs for architecture validation and design teams as well as control and calibration workflows.
  • Establish clear validity ranges assumptions parameter provenance and fidelity levels and maintaincoherence among logical physical and control models as each evolves.
• Drive model validation and closure
  • Partner with validation design and subsystem teams to compare model predictions againstcomponent subsystem and integrated-system measurements.
  • Quantify prediction error and uncertainty usingsensitivity analysis Monte Carlo methods uncertainty propagation and statistical inference where appropriate.
  • Investigate model-to-hardware discrepancies identify missing physics or incorrect assumptions and drivemodel closure with documented evidence.
• Build usable simulation capabilities that scale
  • Develop maintainable modular simulation software inPython with automated tests version control clear APIs and reproducible execution.
  • Provide auser-friendly interface - such as documented Python APIs configuration-driven workflows command-line or graphical tools templates and clear visualization/reporting - so users across the organization can configure and run approved analyses with minimal support.
  • Create versioned component and subsystem model libraries that remain synchronized withrequirements characterization data system configurations and hardware revisions while improving execution efficiency without compromising accuracy or traceability.
  • Create a workflow that enablesother engineers and domain experts to contribute component subsystem and detailed-physics models while maintaining common interfaces review rigor traceability and quality standards.
• Partner cross-functionally and communicate clearly
  • Work closely with architecture validation design photonics electronics controls calibration detailed physics modeling and systems engineering teams to define model needs boundaries and interfaces.
  • Turn ambiguous performance questions into well-scoped modeling studies with clear assumptions confidence bounds and decision-relevant outputs.
  • Communicate model behavior limitations dominant sensitivities and recommended actions throughclear documentation and concise technical and executive updates.

Experience/Qualifications:

• Education & experience
  • MS in Systems Engineering Applied Mathematics Physics Applied Physics Electrical Engineering Computer Engineering or a related field with10 years of relevant industry experience or
  • PhD in a similar field with6 years of relevant industry experience.
• Systems-modeling and signal-processing background
  • Strong foundation insystems modeling for complex multi-domain physical systems with the ability to connect component behavior and physical nonidealities to system-level performance metrics.
  • Strong understanding ofsignal processing noise analysis timing and frequency-domain behavior stochastic processes and statistical data analysis.
• Modeling & software
  • Advanced proficiency inPython scientific computing and experience building production-quality simulation or analysis software that is usable by engineers beyond the development team.
  • Demonstrated experience withgraph-based system representations numerical simulation and model validation for complex physical systems.
  • Experience using and championingmodern agentic software-development best practices.
  • Proficiency withmodern version-control tools and collaborative workflows particularly Git including branching code review and managing contributions from multiple developers.
• Collaboration & communication
  • Exceptional written and verbal communication skills; able to explain model assumptions uncertainty limitations and technical conclusions to both domain experts and system-level decision makers.
• Mindset
  • Rigorous and intellectually curious; comfortable working across abstraction levels challenging assumptions and iterating as designs and measured data evolve.

PsiQuantum provides equal employment opportunity for all applicants and employees. PsiQuantum does not unlawfully discriminate on the basis of race color religion sex (including pregnancy childbirth or related medical conditions) gender identity gender expression national origin ancestry citizenship age physical or mental disability military or veteran status marital status domestic partner status sexual orientation genetic information or any other basis protected by applicable laws.

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