AI/ML Embedded Software Engineer

Overview

Little Place Labs is reimagining how satellites process and deliver intelligence from orbit. We specialize in satellite edge computing, developing advanced solutions that process data directly on board, enabling real-time analysis, rapid decision-making, and a significant reduction in data downlink needs. Our vision is to turn satellites into autonomous, intelligent systems that interpret data instantly, unlocking advantages across defense, environmental monitoring, and global communications from space. Based across the US, Europe, and India, our team solves complex challenges in earth observation, space situational awareness, and autonomous satellite operations.

Role

Embedded Software Engineer with 3–6 years of experience who thrives at the intersection of AI/ML, embedded systems, and containerized software delivery. This is a hands-on software development role where you will design, implement, and optimize embedded software solutions for AI/ML workloads on NVIDIA, Xilinx, and Microchip platforms. You will build and maintain Linux-based environments, write integration libraries, and enable containerized deployment of applications on constrained edge devices. You will work under the Head of Engineering and the CTO, contributing to system integration and actively developing the embedded software stack that powers our edge intelligence solutions in space. This is a remote-first position requiring excellent technical communication to collaborate across global teams and partner satellite operators.

Why Join Us

• Be at the cutting edge of Edge AI in space, shaping the future of real-time satellite intelligence.
• Work with modern embedded platforms (NVIDIA, Xilinx, ARM, RISC-V) in space-based AI/ML.
• Collaborate with a team of ambitious engineers, scientists, and product leaders building breakthrough technology.
• Enjoy the flexibility of a remote-first culture while making a global impact.

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.

Complementary Skills (Nice to Have)

• Networking & Protocols: Knowledge of embedded networking (TCP/IP, UDP, MQTT, gRPC), especially for low-bandwidth or intermittent links.
• Security & Encryption: Familiarity with secure boot, encryption standards, and container security (bonus if experience with Post-Quantum Cryptography).
• Cross-Platform Development: Experience with ARM/x86 toolchains, cross-compilation, and Yocto/OpenEmbedded.
• Performance Optimization: Ability to profile embedded workloads and optimize for power, latency, and throughput constraints.
• Scripting & Automation: Bash, Python, and Ansible (good to have) for automating builds, deployments, and system monitoring.
• Debugging & Profiling Tools: GDB, Valgrind, perf, Nsight, and similar tools for low-level performance analysis.
• Satellite/Space Domain Exposure (Nice-to-Have): Experience with telemetry, satellite communications, or aerospace-grade systems.

Requirements

• 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.

How to Apply

Interested? Reach out to us at [email protected] with your CV or LinkedIn profile.

Equal Opportunity Employment Information

Little Place Labs is an equal opportunity employer. We consider applicants without regard to race, color, religion, national origin, age, sex, marital status, ancestry, disability, veteran status, gender identity, or sexual orientation.