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Instrumentation Physicist: Digital Twin

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: xLight Inc.
Full Time position
Listed on 2026-10-17
Job specializations:
  • Software Development
    Software Engineer, AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 100000 - 145000 USD Yearly USD 100000.00 145000.00 YEAR
Job Description & How to Apply Below

xLight is building the world's most powerful laser to revolutionize semiconductor lithography, metrology, and other critical applications. Our approach is to harness the power of free-electron lasers by building on accelerator technology currently used at scientific facilities around the world. In extending this technology, we are developing industrial-grade light sources, engineered for continuous operation to meet the sophisticated demands of next-generation patterning, metrology, and inspection applications.

Join us in this new revolution!

At xLight, we hire exceptional talent and exceptional means more than a strong résumé. How we achieve results is just as important as the results themselves, which is why attitude and character matter as much as technical skill. We believe great talent is widely distributed and not confined to a particular school or background. We seek individuals who demonstrate ownership, a spirit of collaboration, technical curiosity, and a genuine willingness to learn and grow - guided by our core values of Respect, Integrity, Creativity, and Engineering Excellence.

We don't just hire what someone can do today; we hire for who they are and who they are becoming.

What We Need — and Why It Matters

The goal is to be a digital twin of the accelerator. The first step is virtual commissioning: tune a simulated machine to specification using only what its instruments can measure. This role makes each simulated instrument read what the real instrument would read, with the same noise, offsets and calibration errors.

The twin is a shared project. Accelerator Physics owns the beam dynamics and the error budget. The ML team owns surrogate models, fast solvers, and anomaly detection. This role is in the Diagnostics team and owns the instrument models.

What You'll Do
  • - Model each diagnostic from physics, from the beam through the pickup, front-end electronics and digitizer to the processed reading. Include noise, offsets, nonlinearity and calibration errors.
  • - Validate each model against bench and machine data, and report how well it predicts the real readings.
  • - Turn models that others write into tested, reusable parts.
  • - Commission the diagnostic systems in simulation before they meet beam: calibration, resolution, and the measurement procedures that use them.
  • - With Accelerator Physics, develop the tuning procedures that depend on these measurements, and test them on simulated machines with unknown errors.
Integration
  • - Serve each instrument model through EPICS with the same PVs as the real instrument, so that operator software runs the same against the twin and against the machine.
  • - Connect instrument readout to the twin, with the team's Electrical, FPGA and Controls engineers.
Simulation software
  • - Build and maintain the instrument models in the shared twin code base, and keep them correct and fast as the code base grows.
  • - Review code from other contributors, including code written by AI agents.
  • - Contribute to the beam dynamics codes the twin uses (Bmad / Tao, Impact, Genesis) where the instrument models need it.
  • - With the ML team, infer beam properties that no single instrument measures, from several measurements and a model.
What We Are Looking For
  • - Ph.D. in Physics or related field, or equivalent experience
  • - Strong software engineering in Python: structure, testing (pytest), packaging, code review, including review of code written by AI agents.
  • - The Python scientific stack:
    Num Py, Sci Py, Matplotlib, etc.
  • - Scientific or numerical computing where the result must be physically correct.
  • - Physics depth, from a degree in physics or a related field or from demonstrated work.
  • - Knowledge of how measurement instruments work, from physical signals through electronics to digitized…
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