Senior Signal and Sensor Modeling Engineer - Onsite Tucson

RTX

San Jose (CA)

On-site

USD 87,000 - 165,000

Full time

14 days+

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Benefits offered by this job

Relocation assistance

Job summary

RTX is seeking a Sr. Systems Engineer - Signal and Sensor Modeling in Tucson, AZ for onsite work. You will develop physics-based modeling solutions in the EO/IR/RF domain and contribute to AI-ready hardware and software for defense applications.

You will collaborate with cross-functional teams, deploy cutting-edge modeling, and mentor peers while advancing energy transport and radar concepts in a dynamic environment.

Qualifications

  • Degree in Engineering, Science, Physics, Mathematics, or a related STEM field.
  • Experience with object-oriented design in C++, C, and MATLAB or Python for data evaluation.
  • Experience with UNIX/Linux, Apple OS, or Windows command line.
  • Experience in EO/RF domains such as optics, radar, or signal processing.
  • Eligible for Interim Secret clearance; U.S. citizenship required.

Responsibilities

  • Champion novel modeling techniques for advanced systems.
  • Develop new C++ models in extensible, maintainable form.
  • Apply EO/RF phenomenology in software implementations.
  • Enable customer success through modeling solution adoption.
  • Work across languages and build environments within a product.
  • Research novel EO/RF modeling approaches.
  • Coordinate with multiple teams to solve complex software/physics problems.
  • Mentor teammates on EO/RF topics.

Skills

C++
Python
Unix/Linux
Signal processing

Education

STEM degree (Engineering/Science/Math)

Tools

MATLAB
OpenGL
CUDA
Make/CMake build systems

Job description

RTX is seeking a Sr. Systems Engineer - Signal and Sensor Modeling in Tucson, AZ for onsite work. You will develop physics-based modeling solutions in the EO/IR/RF domain and contribute to AI-ready hardware and software for defense applications.

You will collaborate with cross-functional teams, deploy cutting-edge modeling, and mentor peers while advancing energy transport and radar concepts in a dynamic environment.

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