Who We Are: Join Our Team The Tactical Aerospace team is a premier supplier for avionics and aerospace technology for new and legacy DoD systems. If you like avionics, radar systems, or even supporting EW & SIGINT systems, Tactical Aerospace is the place to be. Tactical Aerospace is also the key research group for cutting edge Neuromorphic and Cognitive AI to apply toward DoD systems. We are on the cutting edge in Neuromorphic/Cognitive AI. Come Join Us Location is in San Antonio, TX or Dayton, OH. Objectives of this Role: This role will be part of our Neuromorphic Computing/Cognitive AI research and development team and will help drive strategies and implementations of our AI solutions to meet our customers’ expectations. Support the development, algorithm selection, machine learning (ML), and test of AI as applied to Systems, UAS, Avionics, EW, and/or aerospace subsystems. This includes implementing SNN's onto Neuromorphic hardware (such as Intel's Loihi 2). Perform Literature reviews, interface with academic institutions, write proposals and implement/deploy those systems. Write code (python, C) to implement AI systems. Includes ML the testing. Will work on other non-AI initiatives and programs. Daily and Monthly Responsibilities: Develop Solutions for AI systems and embedded aerospace/avionics systems and subsystems. Will work on 2nd and 3rd Gen AI systems (Neuromorphic Computing). Will work on Neuromorphic Hardware (Loihi 2) or other chips as necessary. Develop Solutions for neuromorphic systems, EW, SigInt, Situational Awareness, Drones (UAS/UAV), Avionics, AI/ML sensor correlation/fusion, etc. Develop data flows and data analytics. Support engineering programs across the Tactical Aerospace department. Requirements: Requires a PhD in Computer Engineering, Electrical Engineering, AI, or equivalent. 0 years: PhD / university experience developing AI through utilizing C, Python, Tensor Flow, Keras, PyTorch, or other AI development environments. Must have knowledge of appropriate algorithm/method selection and ML/Training. Must have classroom experience in Spiking Neural Networks. Academic experience writing Python and/or C++ with some data analytics. A valid/clear driver's license is required.