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Saxon Global

Digital Processing

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Job Description

Digital Processing

Digital Signal Processing Software Engineer IIDemonstrated ability in related Digital Signal Processing engineering discipline. Supports engineering efforts that provide engineering, technical, and managerial direction for problem definition, analysis, requirement development, and implementation for complex systems in the engineering discipline required to meet technical requirements. Participates in efforts that develop recommendations and advice on system development, improvements, optimization, or support efforts.

Responsibilities:
  • Design, develop, and optimize DSP algorithms for signal acquisition, processing, and analysis.
  • Implement DSP algorithms in software using programming languages such as Python, C/C++,
  • Conduct simulations and perform data analysis to validate algorithm performance and effectiveness.
  • Work closely with User Interface Developers to integrate DSP solutions into systems and platforms.
  • Participate in code reviews, documentation, and continuous improvement activities.
  • Stay abreast of the latest advancements in DSP techniques, tools, and technologies.
Education Requirements:

Bachelor's degree in computer science, Software Engineering, Electrical Engineering, or related field with an emphasis on Digital Signal Processing. Can substitute AS/AA or 2yr Tech School with 5 years experience; or BA in relevant technical area with 3 years experience

Certification Requirements:
N/ASecurity Clearance Requirements:

Top Secret clearance

Qualifications:
Required:
  • Bachelor's degree in computer science, Software Engineering, Electrical Engineering, or related field with an emphasis on Digital Signal Processing
  • 3-7 of hands-on experience in DSP algorithm design and implementation
  • U.S. Citizenship
  • TS/SCI Clearance with the ability to obtain a CI Poly
  • Strong programming experience in C++ and Python
  • Experience developing applications in Linux environments.
Desired:
  • Familiarity with GPU development, including CuPy and CUDA.
  • Accelerated python libraries, numpy, scipy
  • High-Performance Computing (HPC) or near-realtime processingCore Engineering SkillsDevelopment Environment
  • Experience with:
  • Git
  • CI/CD pipelines
  • Docker containers
  • Automated testing
  • Familiarity with:
  • Linux command line
  • Debugging tools
  • Performance profiling