Little Place Labs is reimagining how satellites process and deliver intelligence from orbit by developing advanced solutions that process data directly on board, enabling real-time analysis, rapid decision-making, and a significant reduction in data downlink needs. The company aims to turn satellites into autonomous, intelligent systems that interpret data instantly, unlocking critical advantages across defense, environmental monitoring, and global communications.
Requirements
- 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.
- Experience with ARM/x86 toolchains, cross-compilation, and Yocto/OpenEmbedded.
- Knowledge of embedded networking (TCP/IP, UDP, MQTT, gRPC), especially for low-bandwidth or intermittent links.
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.
Other
- 3–6 years of experience, who thrives at the intersection of AI/ML, embedded systems, and containerized software delivery.
- Ability to work independently in a remote-first environment, coordinating across time zones.
- Excellent technical communication to collaborate across global teams and partner satellite operators.
- Bachelor’s/Master’s degree in Computer Engineering, Electrical Engineering, Computer Science, or equivalent.
- Strong debugging, problem-solving, and communication skills.
