Embedded Software Engineer - Edge ML/Low SWaP Systems
Expedition Technology, Inc.
Herndon, VA, United States
about 1 month ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source
Tech stack
Algorithm Design
Computer Vision
Nvidia CUDA
Embedded Software
Field-Programmable Gate Array (FPGA)
Python (Programming Language)
Linux System Administration
Machine Learning
Tensorflow
Signal Processing
Software Deployment
Data Processing
+8 more
Real Time Systems
Pytorch
Containerization
ONNX (Open Neural Network Exchange) Format
Production Code
Machine Learning Operations
Multiaccess Edge Computing
Docker
Job description
We are seeking an Embedded Software Engineer to support the deployment of advanced data processing and machine learning solutions to low size, weight, and power (SWaP) systems. This role focuses on optimizing and deploying algorithms to GPU-enabled embedded platforms (e.g., NVIDIA Jetson) for real-time applications. What You’ll Do
- Deploy and optimize computer vision, signal processing, or data processing algorithms on embedded hardware
- Improve real-time, low-latency performance of ML pipelines on constrained systems
- Profile CPU/GPU performance and identify system bottlenecks
- Collaborate on algorithm selection based on hardware constraints
- Containerize and deploy solutions using tools like Docker
- Work in Linux-based environments and contribute to production-quality code
- Partner with ML and software engineers to transition models into operational environments
Requirements
- United States Citizenship - for US Government security clearance eligibility
- Active Top Secret/SCI (TS/SCI) security clearance
- Experience deploying software or algorithms to embedded or edge systems
- Proficiency in Python or ability to learn quickly
- Experience working in Linux environments
- Experience optimizing performance in constrained environments
-
Strong problem-solving skills across software and hardware domains Preferred Qualifications
- Experience with NVIDIA Jetson or similar GPU-enabled embedded platforms
- Experience with video or signal processing pipelines
- Familiarity with CUDA and CPU/GPU profiling
- Experience with Docker or containerization
- Experience with ML frameworks such as PyTorch or ONNX
- Prior experience working on ML-focused teams Additional Information This role is focused on embedded systems with GPU acceleration rather than traditional microcontroller or FPGA-centric work. Candidates should be comfortable working across the full lifecycle of algorithm development and deployment in performance-sensitive environments. Work Environment & Culture At EXP, we value collaboration, continuous learning, and innovation. Engineers are encouraged to leverage modern tools and technologies, including AI-assisted development, while working closely with teammates to solve challenging mission problems.
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