System Modeling and Simulation Lead (Quantum Systems)

Entangled Future; Milpitas (CA); Hybrid; USD 180,000 - 260,000; Full time

Job summary

PsiQuantum in Milpitas, CA seeks a System Modeling and Simulation Lead for quantum systems. This senior role focuses on creating high-fidelity models linking component behavior to system performance in a remote-friendly setup within the hardware engineering domain.

Qualifications include MS or PhD with extensive industry experience, strong modeling skills, and expertise in signal processing, statistics, and Python-based simulation tools.

Qualifications

• MS in related field with 10+ years of industry experience, or PhD with 6+ years.
• Strong foundation in systems modeling for multi-domain physical systems.
• Expertise in signal processing, noise and timing/ frequency-domain behavior, stochastic processes, and statistics.

Skills

systems modeling

signal processing

noise analysis

timing & frequency-domain

stochastic processes

statistical data analysis

Python

graph-based modeling

numerical simulation

model validation

agentic software practices

Education

MS in Systems Engineering / Applied Mathematics / Physics / Electrical Engineering or related field

10+ years of relevant industry experience

PhD in a similar field

related field with 6+ years experience (PhD alternative)

Tools

Python

Job description

System Modeling and Simulation Lead (Quantum Systems) at PsiQuantum, Milpitas, California, United States (remote). A lead-level full time position in the Engineering team, listed under hardware engineering.

PsiQuantum's 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 architecture and approach is based on silicon photonics. By leveraging the 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: photons don't feel 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 up. In 2025, PsiQuantum closed a $1 billion funding round that valued the company at $7 billion. In 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 Initiative, PsiQuantum's most 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 O'Brien, now Executive Chairman, lead a team and board that reflects how seriously the world is taking this build, joined this year by Intel's Lip-Bu Tan and Atomico's Niklas Zennström. PsiQuantum also develops the algorithms and software needed to make these systems co

Requirements

• Education & experienceMS in Systems Engineering, Applied Mathematics, Physics, Applied Physics, Electrical Engineering, Computer Engineering, or a related field with10+ years of relevant industry experience, orPhD in a similar field with6+ years of relevant industry 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.
• 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.
• 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.