Primary ResponsibilitiesIn this role, you will support the design, modeling, and experimental validation of infrared meta-optic systems integrated with digital reconstruction and inference algorithms. You will develop and apply computational imaging models that connect optical design, image formation, detector response, calibration, image reconstruction, and downstream inference performance.
You will contribute to the development of simulation tools and algorithms for analyzing hybrid optical-digital imaging systems, including forward image-formation models, inverse-problem formulations, reconstruction algorithms, and end-to-end optimization of optical and computational parameters. You will also support design trades and system-level evaluations involving image quality, signal-to-noise ratio, reconstruction fidelity, classification performance, robustness, and computational complexity.
Working closely with senior engineers and cross-functional teams, you will help evaluate and mature emerging optical technologies, including metaoptics and optical computing systems, analyze experimental data to inform design decisions, and document results to support internal R&D and program efforts.
This position includes both analytical and experimental responsibilities, with an emphasis on modeling and algorithm development. The ideal candidate is comfortable working across optical simulation, computational imaging, machine learning, and laboratory environments and is interested in developing integrated optical-digital sensing systems.
Basic Qualifications- BS degree in Physics, Materials Science, Optics, or a related field with 8+ years of prior relevant experience or MS with 6+ years of prior relevant experience. May possess a Doctorate in technical domain.
- Demonstrated research or development experience in computational imaging or a closely related field
- Experience with Fourier optics, wave propagation, diffraction, and coherence theory
- Experience with optimization methods used in computational imaging, including gradient-based optimization, regularization, or statistical estimation
- Familiarity with machine-learning-based reconstruction or inference methods, including convolutional neural networks or related architectures
- Experience programming in Python using scientific-computing and machine-learning tools such as NumPy, SciPy, PyTorch, JAX, or TensorFlow; experience with MATLAB or C++ may also be applicable
- Strong analytical and problem-solving skills with attention to detail
- Must be a U.S Citizen
- Must be able to obtain and maintain a Secret security clearance.
Preferred Qualifications- Active Secret clearance with ability to obtain a higher-level clearance (TS/SCI)
- Experience designing or modeling optical systems using Zemax OpticStudio, CODE V, FRED, or equivalent software
- Experience developing and evaluating machine-learning-based image reconstruction, detection, or classification systems
- Experience working in a laboratory environment, including optical alignment, imaging-system testing, detector characterization, or optical characterization
- Familiarity with diffractive optics, meta-optics, metasurfaces, or nanophotonic inverse-design
- Experience with electromagnetic modeling tools such as COMSOL, Ansys Lumerical, or equivalent
- Record of research contributions demonstrated through publications, patents, conference presentations, or development of relevant computational-imaging systems
Original Posting:August 19, 2026
Pay Range:Pay Range $107,900.00 - $195,050.00
The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
