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.