Data Scientist - Edge AI & Embedded Systems - Reston
Core
Develop and deploy AI/ML models (computer vision, LLMs) for mission-specific use cases on resource-constrained embedded hardware in air-gapped environments.
Role type
Senior IC Edge AI & Embedded Systems Engineer
Builds
Offline-native data and machine-learning pipelines deployed on embedded hardware
Domain
Defense/Intelligence, Edge AI, Embedded Systems
Deliverable
production ML models
Required skills
AI/ML algorithms, Computer Vision, Large Language Models, Python, Linux, Docker, Model Optimization (quantization, pruning), Embedded Systems, RF/Signal Analysis
Preferred skills
DoD/IC support experience, Dataset management, Open-source AI tools, x86/ARM/SoC/RISC-V architectures, Single-board computers, C/C++/Java, Software-defined radios, Offline MLOps
Technologies
PyTorch, TensorFlow, NumPy, pandas, scikit-learn, TensorRT, ONNX Runtime, llama.cpp, Bash, Git, GitHub, GitLab, Hugging Face, Kaggle, ARM, Arduino, Raspberry Pi, BeagleBoard, NVIDIA Jetson
Responsibilities
Source, curate, clean, and label datasets from open-source repositories and operational sensor data. Train, fine-tune, and assess AI/ML models for mission-specific use cases. Develop evaluation methods and metrics to measure model accuracy, latency, and reliability. Optimize models for resource-constrained hardware. Build and deploy offline-native pipelines in containerized environments. Configure and troubleshoot Linux-based embedded systems. Explore and analyze data from digital communications systems. Assess open-source AI software and models. Prepare supporting documentation including model-performance reports.
