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Embedded Systems Developer
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This role is focused on developing and optimizing embedded software solutions for AI/ML workloads on NVIDIA, Xilinx and Microchip platforms. You will be responsible for building and maintaining Linux-based environments, writing integration libraries, and enabling containerized deployment of applications on constrained edge devices.
As an Embedded Software Engineer, you will work under the Head of Engineering and the CTO to contribute to managing development kits and system integration, as well as actively developing the embedded software stack that powers our edge intelligence solutions in space.
Key Responsibilities:
- Linux Expertise: Configure and manage Linux environments (Ubuntu and custom distributions), including kernel modules, system tuning, cross-compilation, and deployment scripts.
- AI/ML Optimization and Testing on the Edge: Integrate ML models into embedded systems; collaborate with Data Science teams to enable deployment on resource-constrained hardware.
- Low-Level Engineering: Work with C, C++, and Python to build and optimize drivers, OS-level services, and low-level libraries for ML acceleration.
- Containerization: Develop, test, and optimize Dockerized applications for AI/ML workloads, ensuring portability, efficiency, and compliance with partner satellite company requirements.
- Embedded Systems Ownership: Manage and maintain Edge AI development kits (NVIDIA Jetson, Xilinx platforms, etc.), ensuring smooth workflows for in-orbit simulation and testing.
- Hardware Acceleration: Leverage CUDA, cuDNN, TensorRT (NVIDIA) and Vitis AI / OpenCL (Xilinx) to accelerate workloads.
- Systems Integration: Interface with satellite payload hardware and ground systems; debug integration issues across hardware, OS, and application layers.
- CI/CD for Edge: Develop pipelines for automated testing and deployment of embedded software builds.
- Documentation & Support: Maintain clear documentation of configurations, workflows, and deployment practices; support partner satellite companies in deploying our dockerized products.
- Version Control & Collaboration: Git/GitHub, code review best practices, and working in distributed development teams.
To be successful in this role, you should have:
- 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.
Individuals seeking employment at Little Place Labs are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.
