Role
Overview
- As a Space Edge Computing Engineer, you
- will design, develop, and optimize onboard satellite processing pipelines that
- run on resource-constrained space-grade computing platforms. You will help
- enable real-time data processing, bandwidth optimization, and autonomous
- decision-making in space.
Key
Responsibilities
- Design and optimize onboard processing
pipelines for SAR and MSI payloads.
- Convert raw payload data into Level-1 and Level-2 products directly on-orbit.
- Optimize compute, memory, power, and storage usage on satellite hardware.
- Develop high-performance software using C++, Rust, and Python.
- Develop high-performance software using frameworks like CUDA/OpenCL, ONNX Runtime etc.
- Accelerate algorithms on FPGA, ARM, GPU, and AI accelerator architectures.
- Implement data compression, transmission optimization, and edge AI inference.
- Build simulation and validation frameworks for pre-flight testing.
- Collaborate with payload, avionics, mission operations, and AI teams.
Requirements
- Bachelor's or Master's in Computer
Science, Electronics, Aerospace, Robotics, or related field.
- 1+ years experience in relevant fields.
- Strong proficiency in C++ and Python.
- Experience with embedded systems, Linux, performance optimization, and
parallel computing.
- Basic understanding of image processing, signal processing, or computer
vision fundamentals.
Benefits
- Experience in SAR processing, remote
sensing, geospatial analytics, FPGA development, CUDA/OpenCL, ONNX Runtime,
TensorRT, or edge AI deployment.
- Familiarity with satellite systems, space-grade hardware, CubeSats, or
avionics software.
Job description provided by GalaxEye.
View the original posting