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# Quantum Information Physicist for AI Model Training

- **Company:** Careerjet All Rights Reserved
- **Location:** Washington, DC, United States (Remote available)
- **Salary:** $166,400.0 - $332,800.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Machine Learning, Visual Systems
- **Published:** August 4, 2026
- **Apply:** https://www.careerjet.com/job/register/usbf33281c82a64750b9a4f6c55717b656

## About the Role

* Advanced degree such as a PhD, or equivalent research experience, in AMO physics, quantum optics, or quantum information science preferred.
 * Proven expertise with Bogoliubov transformations, covariance-matrix formalism, and quantum noise analysis.
 * Hands-on familiarity with sideband photocurrent spectra and homodyne detection methods.
 * Experience modeling quantum optical loss mechanisms, including using fictitious beamsplitter techniques.
 * Demonstrated ability applying squeeze-parameter hyperbolic identities to characterize squeezing and entanglement, in practical research or experimental analysis.
 * Experience with cascaded parametric amplifiers, SU(1, 1) interferometry, or two-mode squeezing is highly valued.

Work Terms

 * Role type, contractor.
 * Location, remote.
 * Assignments and role (Solver, Auditor, Adjudicator) will be tailored to your subfield specialization, experience level, and demonstrated practical ability with the listed methods.
 * No prior AI or machine learning experience required, domain knowledge in AMO and quantum information is the primary requirement.

Compensation
Pay range: $80.00 to $160.00 per hour. Eligibility

 * Must be able to work as an independent contractor in a remote engagement.
 * Strong domain expertise in AMO physics, quantum optics, or quantum information science is required.

## Description

Contribute AMO and quantum information expertise to a research-focused project that benchmarks and models quantum optical systems. The work centers on cascaded optical parametric amplifiers, SU(1, 1) interferometers, two-mode squeezing, and the impact of realistic loss on entanglement and noise. Deliverables will shape how advanced models learn and reason about frontier quantum optics concepts. Key Responsibilities

 * Analyze and model cascaded optical parametric amplifiers and SU(1, 1) interferometric setups under realistic loss mechanisms.
 * Apply Bogoliubov transformations and covariance-matrix methods to quantify quantum correlations and noise properties.
 * Derive and interpret sideband photocurrent spectra using homodyne detection techniques.
 * Model optical loss via fictitious beamsplitters, and benchmark models against theoretical and experimental scenarios.
 * Use squeeze-parameter hyperbolic identities to characterize entanglement and squeezing performance in lossy systems.
 * Contribute in one of several roles, including Solver, Auditor, or Adjudicator, with assignments matched to your subfield specialization, experience, and demonstrated hands-on ability with the specified methods.
 * Provide clear, research-grade explanations and analyses that can be used to train and evaluate next-generation AI systems, no prior AI experience required.


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