Quantum Device Modelling Engineer - Equity & Flexible Hours

Socket.dev

Los Angeles (CA)

Hybrid

USD 130,000 - 160,000

Full time

9 days ago

Get more replies from employers

Send a job-specific resume in minutes.

Benefits offered by this job

Equity participation

Health insurance

Retirement plan

Flexible work arrangements

Professional development

Collaborative environment

Job summary

Diraq is developing the world’s most scalable quantum computing architecture and seeks a talented Device Modelling Engineer to lead simulation studies for next-generation semiconductor quantum devices. You’ll work with materials scientists, process engineers, device engineers, and researchers to transform complex questions into actionable modelling projects.

The role focuses on electrostatic and transport modelling, numerical methods, data-driven decisions, and tool development to support

Qualifications

Bachelor’s, Master’s, or PhD in Physics, Electrical Engineering, Materials Science, Applied Mathematics, Engineering Physics, or related technical discipline.
Strong analytical and problem-solving skills with the ability to tackle complex technical challenges.
Foundational knowledge of semiconductor physics and devices, including charge transport, electrostatics, device operation, and process technologies.
Experience using advanced simulation or numerical computing environments (TCAD, FEA tools, EM simulators, Python, MATLAB, or equivalent).
Experience developing scripts, automating workflows, and analyzing large datasets.
Understanding of numerical methods and physical simulation principles.
Strong written and verbal communication skills to explain complex concepts.

Responsibilities

Develop, maintain, and improve simulation workflows for semiconductor devices and process technologies.
Perform electrostatic, transport, and physics-based modelling of nanoscale semiconductor devices.
Evaluate design trade-offs, variability mechanisms, and sensitivity to process changes.
Analyze simulation and experimental datasets to identify key performance drivers and engineering opportunities.
Validate simulation predictions against measured device performance and refine models accordingly.
Collaborate with multidisciplinary teams to support technology development and product roadmaps.
Present technical findings and recommendations to engineering and scientific stakeholders.
Contribute to continuous improvement of modelling methodologies, tools, and automation frameworks.