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 interpret photonic electronic and mixed-domain system descriptions component models characterization data and system configuration inputs.
  • Translate component and interface performance - including loss noise jitter drift and stability crosstalk and false-count rates - into end-to-end predictions of key quantum system metrics.
  • Develop models that support architecture trades requirement allocation performance budgeting and design decisions before full hardware is available.
• Develop coherent reusable system abstractions
  • Create reduced-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 the necessary 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 maintain coherence 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 against component subsystem and integrated-system measurements .
  • Quantify prediction error and uncertainty using sensitivity analysis Monte Carlo methods uncertainty propagation and statistical inference where appropriate.
  • Investigate model-to-hardware discrepancies identify missing physics or incorrect assumptions and drive model closure with documented evidence .
• Build usable simulation capabilities that scale
  • Develop maintainable modular simulation software in Python with automated tests version control clear APIs and reproducible execution.
  • Provide a user-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 with requirements characterization data system configurations and hardware revisions while improving execution efficiency without compromising accuracy or traceability.
  • Create a workflow that enables other 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 through clear 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 with 10 years of relevant industry experience or
  • PhD in a similar field with 6 years of relevant industry experience.
• Systems-modeling and signal-processing background
  • Strong foundation in systems modeling for complex multi-domain physical systems with the ability to connect component behavior and physical nonidealities to system-level performance metrics.
  • Strong understanding of signal processing noise analysis timing and frequency-domain behavior stochastic processes and statistical data analysis .
• Modeling & software
  • Advanced proficiency in Python scientific computing and experience building production-quality simulation or analysis software that is usable by engineers beyond the development team.
  • Demonstrated experience with graph-based system representations numerical simulation and model validation for complex physical systems.
  • Experience using and championing modern agentic software-development best practices .
  • Proficiency with modern 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.

Note: PsiQuantum will only reach out to you using an official PsiQuantum email address and will never ask you for bank account information as part of the interview process. Please report any suspicious activity to .

We are not accepting unsolicited resumes from employment agencies.

Base pay is one part of the total compensation package. Full-time roles are eligible for equity and compensation ranges reflect the cost of labor across multiple U.S. geographicmarkets and we pay based on defined geographic zones. This position may be filled withinone of the followingU.S. geographic zones each with its own salary range.

Actual compensation may vary outside of these ranges and is dependent onvarious factorsincluding but not limited to a candidates qualifications relevant education and training competencies experience geographic location business needs and internal equity. Your recruiter can share more details about the salary range applicable to your location during the hiring process.

• Zone 1- Bay Area and NYC

• Zone 2-Examples include LosAngelesandWashington DC

• Zone 3-Examples include Austin Chicagoand Sacramento

• Zone 4-Examples include Nashville and Phoenix/Tempe and manyremote locations

This position includes the following benefits: competitive health coverage for you and your dependents 401(k) with company match equity grants access to financial wellness tools and planning resources wellness benefits family support programs life and disability insurance paid leave programs company-designated paid holidays discretionary time off (DTO) and an end-of-year company shutdown. Some of these benefits have eligibility requirements and may vary based on location role or employment status. Many of these benefits are subsidized or fully paid for by the company.

The e s timated annual base salary rangefor this role is:

Zone 1

$208300 - $244700 USD

Zone 2

$187400 - $220200 USD

Zone 3

$166600 - $195800 USD

Zone 4

$145800 - $171300 USD