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RTX Corporation

Systems Engineer II - Signal Processing

RTX Corporation

Published 07 May 2026
Tucson, AZ, USA
69K - 131K USD Annual
Remote
Onsite

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Role Highlights

Languages used

C
C++
C#
Java
MATLAB
Python

Key skills

Integrations
Electrical Engineering
Signal Processing
Security
Operations
Research
Navigation
Modelling
ProtoTyping
Testing
Data
Startup
Mathematics
Physics
Devops

Tools, Libraries and Frameworks

Azure DevOps
Flow
HTTP

Description

The role involves collaborating on the design, development, prototyping, integration, and testing of radio frequency or electro-optical/infrared algorithms and models. Professionals in this position will use and modify simulations to assess the performance of signal processing algorithms. They will participate in engineering lab environments to verify and validate sensor models against established requirements. The work includes integrating algorithms into hardware and supporting all development phases from program start-up to live-fire testing.

Required Qualifications and Skills

Candidates must possess a Bachelor’s degree in a STEM field and at least two years of relevant experience. Proficiency in C, C++, C#, or Java is required, along with experience in algorithm design, implementation, analysis, testing, or optimization. Applicants must be U.S. citizens capable of obtaining and maintaining an Interim Secret U.S. government security clearance. The role requires the ability to work onsite and participate in lab environments for hardware and software integration.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

RTX Corporation

Size

125656

HQ

Arlington, US

Description

RTX is comprised of three market-leading businesses Collins Aerospace, Pratt & Whitney and Raytheon working as one to answer the biggest questions and solve the hardest problems in aerospace and defense.

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