Radar Algorithm Developer at IERUS Technologies, Inc.
Huntsville, AL
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Jul 20, 2026
Huntsville, AL
Jul 21, 2026
What this job asks for AI summary
A research and engineering role focused on developing and applying machine learning and AI solutions across defense-relevant domains such as radar signal processing, electronic warfare, RF/optical systems, and image processing. The work involves algorithm development, rapid prototyping, and GPU-accelerated computing. It suits candidates with a background in electrical engineering, computer science, or applied mathematics who hold or can obtain a U.S. security clearance.
Mid level · 2+ years · Huntsville, AL · Bachelor's required · Secret clearance · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $114,269 (middle half $86,859–$140,248).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 29, 2026. It is a model, not a headcount.
Why we read it this way (10)
The role sits between data science (ML/AI algorithm development) and applied software engineering for defense domains; 15-2051 was chosen as primary because ML/AI algorithm development and scientific application are the explicit core of the role, with 15-1252 as a close runner-up given the implementation and prototyping emphasis.
The minimum experience requirement is 2 years (with an MS) or 3 years (with a BS); 2 years is used as the overall years minimum per the lower bound of the MS path.
Degree requirement: the JD offers two paths — MS+2 yrs or BS+3 yrs. A Bachelor's is the lowest formal degree that satisfies either path, so the degree requirement is set to Bachelors.
Clearance: the JD states 'Active Secret security clearance, preferred TS clearance and TS/SCI opportunities.' An active Secret is listed as a minimum qualification (hard gate); TS/SCI is preferred. Clearance is set to Secret accordingly.
The 'feature selection, regression, classification, sensor-fusion, time-series analysis, missing data, optimization, recommender systems' list appears under Minimum Qualifications as implementation familiarity; these are methodological concepts rather than named tools, so only the concrete named technologies (Python, R, MATLAB, SVM, TensorFlow, etc.) are extracted as skills.
Supervised ML methods (SVM/SVR, fuzzy systems, tree ensembles, NNs) are required; one primary skill (SVM) is emitted with the others as alternatives since the JD requires experience with 'at least 2' — they are interchangeable options within the same gate.
Deep learning packages (TensorFlow, Theano, Torch/PyTorch, Caffe, Neon) and unsupervised methods appear under Preferred Qualifications and are marked preferred.
GPU acceleration appears in the company narrative/domain description rather than in a qualifications section; marked preferred.
RADAR, signal processing, image processing, SDR, and RF electronics experience all appear under Preferred Qualifications and are marked preferred.
Requires a Secret clearance — the cleared population is a small fraction of this occupation, so the real candidate pool is materially smaller than the estimate below, which does not model clearance.
Read the full posting
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