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AI Optimization Engineer, Edge & Embedded Systems

AI Optimization Engineer, Edge & Embedded Systems

Blue SignalArlington, VA
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Role Title : AI Optimization Engineer, Edge & Embedded Systems

Location : Arlington, VA (Primarily On-site, Hybrid Flexibility Available)

Employment Type : Full-Time

Overview :

A pioneering organization at the intersection of advanced autonomy and national security is seeking a driven AI Optimization Engineer to spearhead the deployment of machine learning models in mission-critical edge environments. From UAVs and aerospace payloads to mobile intelligence systems, this role is vital in enabling real-time AI inference in highly constrained environments—where compute, power, and bandwidth are limited but reliability is non-negotiable.

What You’ll Do :

  • Develop and deploy high-performance AI and machine learning models tailored for embedded and low-power platforms.
  • Convert, compress, and optimize models using advanced tools such as ONNX, TensorRT, OpenVINO, and TVM.
  • Partner with internal R&D teams to transition models from development to real-world applications, bridging the gap between lab innovation and field execution.
  • Enhance neural networks for real-time inference by tuning performance, memory use, and energy efficiency.
  • Integrate AI systems with sensors, controllers, and autonomy frameworks for onboard deployment in disconnected and resource-constrained environments.
  • Perform rigorous profiling, performance benchmarking, and field testing across diverse embedded platforms.
  • Troubleshoot system-level issues and iterate solutions in dynamic, operational conditions.

What You Bring :

  • Bachelor’s, Master’s, or PhD in Computer Engineering, Electrical Engineering, Computer Science, or a related discipline.
  • 3+ years of experience in deploying AI models to embedded, edge, or real-time platforms.
  • Strong skills in C++, Python, and embedded computing frameworks.
  • Expertise in AI model deployment pipelines including conversion, quantization, pruning, and inference optimization.
  • Experience with hardware accelerators such as NVIDIA Jetson, Intel Movidius, Coral, or FPGAs.
  • Understanding of embedded system constraints including latency, thermal budgets, and memory management.
  • Preferred Experience :

  • Exposure to autonomous systems such as drones, field robotics, or aerospace solutions.
  • Hands-on experience with ROS / ROS2 or robotic middleware integration.
  • Familiarity with secure, disconnected, or air-gapped environments with intermittent connectivity.
  • Eligibility for or possession of a U.S. security clearance is strongly preferred.
  • Why Apply :

  • Be part of a high-caliber team deploying AI where it matters most—in the field.
  • Work on impactful projects supporting critical missions in national defense and security.
  • Shape the future of AI-powered autonomy and real-time decision-making at the tactical edge.
  • Enjoy a competitive compensation package, growth opportunities, and the support of a cutting-edge engineering culture.
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