IERUS specializes in technology research, testing, and implementation with core competencies in electromagnetics phenomenology, computational analytics (algorithm acceleration and machine learning), and weapon system engineering. IERUS develops value for our defense and commercial customers through accelerations of the technology life cycle: identifying, creating, transitioning, and producing technologies with integrity of purpose and product. IERUS offers competitive compensation packages, retirement options, and benefits packages. To learn more, please visit www.ierustech.com.
IERUS participates in projects that address weapon systems engineering and the application of advanced machine learning (ML) and artificial intelligence (AI) techniques as well as RF/Optical hardware prototyping and low rate production. We generally seek to apply agile development fundamentals across our corporate portfolio to accelerate technology development timelines. The end goal being early discovery, accelerated development, and high customer engagement.
Description:
IERUS Technologies, Inc., is seeking a Signal Processing Engineer to join a diverse and flexible team. The ideal candidate will have 5 or more years of experience of radar processing, model development and analysis.
Desired Experience
- Radio frequency (RF) static range measurements;
- RF defense radar systems;
- RCS predictions;
- Digital signal processing (DSP);
- Programming (MatLab, Python, C, or similar);
- Active Secret clearance.
Required
- Bachelor's degree (or higher) in Engineering, Mathematics, or Physics;
- 5+ years of experience;
- Written and oral communication skills;
- Active Secret clearance;
- US Citizenship.
Experience considered a plus
- Proficiency in MatLab or similar analysis tools;
- Experience with Unix/Linux;
- Familiarity with RCS prediction tools (Xpatch, Cicero, etc.);
- Familiarity with CAD tools for developing RF signature models (Rhino, Cubit, etc.).
Location:
Crane, IN
IERUS Technologies is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age, or any other federally protected class.
IERUS Technologies participates in E-Verify.
Skills Required
- Bachelor's degree or higher in Engineering, Mathematics, or Physics
- At least 5 years of experience
- Written and oral communication skills
- Active Secret clearance
- U.S. citizenship
- Experience with radar processing, model development, and analysis
- Experience with RF static range measurements
- Experience with RF defense radar systems
- Experience with radar cross-section predictions
- Experience with digital signal processing
- Programming experience with MATLAB, Python, C, or similar languages
- Proficiency in MATLAB or similar analysis tools
- Experience with Unix/Linux
- Familiarity with RCS prediction tools such as Xpatch or Cicero
- Familiarity with CAD tools such as Rhino or Cubit for RF signature models
What We Do
IERUS, at its core, is a high-end technology firm. IERUS recruits and retains a work force of highly skilled and educated engineers, scientists, and mathematicians. While IERUS’s core is electro-optics/infra-red (EOIR) and electromagnetic (EM) technology, IERUS engineers come from various backgrounds. IERUS employees are our most valuable asset, and we are committed to recruiting high caliber personnel. IERUS emphasizes creativity and fosters an environment that encourages employees to pursue technically challenging problems that fit within their interest and capability set. IERUS’s work force education ranges from bachelors through PhDs, specializing in Electrical Engineering, Mechanical Engineering, Physics, and Math. Approximately one quarter of IERUS’s technical staff have PhDs, over three quarters hold a Masters level degree or above, and the remaining have bachelors engineering degrees. This spread means IERUS can apply in-depth technical leadership where needed but has the labor distribution base to solve problems cost efficiently.
