
Chief Embedded Software Architect
4 days ago
Revolutionize the Frontiers of Space Technology
We are on a mission to harness the limitless potential of space-based technologies and utilize them to tackle the world's most pressing challenges. Our team thrives in an environment that fosters innovation, passion, and collaboration.
About the RoleThis is a hands-on software development position where you will design, implement, and optimize embedded software solutions for AI/ML workloads on NVIDIA, Xilinx and Microchip platforms.
Key Responsibilities- Configure and manage Linux environments (Ubuntu and custom distributions), including kernel modules, system tuning, cross-compilation, and deployment scripts.
- Integrate ML models into embedded systems; collaborate with Data Science teams to enable deployment on resource-constrained hardware.
- Work with C, C++, and Python to build and optimize drivers, OS-level services, and low-level libraries for ML acceleration.
- Develop, test, and optimize Dockerized applications for AI/ML workloads, ensuring portability, efficiency, and compliance with partner satellite company requirements.
- Manage and maintain Edge AI development kits (NVIDIA Jetson, Xilinx platforms, etc.), ensuring smooth workflows for in-orbit simulation and testing.
- Leverage CUDA, cuDNN, TensorRT (NVIDIA) and Vitis AI / OpenCL (Xilinx) to accelerate workloads.
- Interface with satellite payload hardware and ground systems; debug integration issues across hardware, OS, and application layers.
- Develop pipelines for automated testing and deployment of embedded software builds.
- Bachelor's/Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or equivalent.
- 3–8 years of hands-on experience in embedded software development.
- Proficiency in C, C++, and Python.
- Deep knowledge of Linux (system internals, drivers, kernel tuning).
- Proven experience with Docker and containerized workflows.
- Experience with NVIDIA Jetson, CUDA, TensorRT, and Xilinx Vitis AI / OpenCL.
- Familiarity with edge AI/ML workloads, model deployment, and performance optimization.
- Strong debugging, problem-solving, and communication skills.
- Ability to work independently in a remote-first environment, coordinating across time zones.
The successful candidate will be highly motivated, have excellent technical skills, and a passion for working in a dynamic environment.
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