Embedded engineer serp_jobs.h1.location_city

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 :

Preferred Experience :

Why Apply :