Senior DSP Engineer

Metrea Management LLCVictor, NY
Onsite

About The Position

We're looking for a Senior DSP Engineer to design, implement, and validate radar signal processing algorithms in production C++. You'll work closely with the Head of RADLAB, R&D staff, and other engineers to turn research concepts into fast, tested, profiled, and reproducible code. This is a small lab doing novel work. You'll see your algorithms run on real hardware, real time, on real missions.

Requirements

  • BS/MS in Electrical Engineering, Computer Science, Applied Math, Physics or a related field.
  • 8+ years implementing signal processing algorithms in C or C++.
  • Strong applied math: comfortable reading derivations and designing and implementing numerical algorithms for computing the results.
  • Experience validating algorithm implementations against analytical derivations, simulated ground truth, or measured data.
  • Software engineering discipline: version control, testing, documentation, code review.
  • Clear technical writing.
  • U.S. Citizenship
  • Ability to obtain and maintain a TS security clearance.

Nice To Haves

  • Radar-specific DSP experience: adaptive beamforming, STAP, pulse compression, or CFAR.
  • Modern C++ fluency (C++17/20, templates, concepts).
  • Python for prototyping, analysis, and test automation.
  • GPU-accelerated signal processing.
  • FPGA experience. HLS (C++-based) is sufficient; RTL is not required. You'll have the opportunity to learn if you haven't done it.
  • Familiarity with SDR platforms or radar hardware-in-the-loop environments.
  • A PhD degree with a thesis in a radar or statistical signal processing topic.

Responsibilities

  • Implement and validate radar signal processing algorithms, such as digital beamforming, signal detection, Doppler estimation, and digital filtering in modern C++.
  • Own the reference processing chain: unit and integration tests, golden vector validation inside our CI/CD pipelines.
  • Run simulation campaigns (Monte Carlo, sensitivity sweeps) and document results.
  • Profile performance and identify numerical stability issues, bottlenecks, and optimization opportunities.
  • Translate mathematical specifications into correct, maintainable, testable code, and push back when the math needs revisiting.
  • Deploy your work onto RADLAB hardware and ensure algorithm designs are feasible under real-time constraints.
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