AI/ML Embedded Software Engineer

Got superpower? This is not just a job. We show up each day ready to explore the unlimited possibilities of space-based technologies and utilise them to combat the most critical problems. We believe that with passion, purpose, risk taking, and willingness to learn, we can make a positive impact on the world. Role - Embedded Software EngineerABOUT LITTLE PLACE LABS 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 don’t just capture data, but interpret it instantly. This capability unlocks critical advantages across defense, environmental monitoring, and global communications, providing insights with speed, efficiency, and security right from space. Based across the US, Europe, and India, our team works on solving complex challenges in earth observation, space situational awareness, and autonomous satellite operations. Our rapidly growing team of mission-driven, space enthusiasts is passionate, innovative, and committed to a better future for planet Earth, the little place that we all call home.WHY JOIN US At Little Place Labs, you will: 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 one of the most exciting application areas: 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.POSITION SUMMARYRemote - Full-Time role - for candidates based in India.Little Place Labs is looking for an 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 be directly responsible for building and maintaining Linux-based environments, writing integration libraries, and enabling containerized deployment of applications on constrained edge devices. You will work under the Head of Engineering and the CTO, contributing not just to managing development kits and system integration, but also to 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.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 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 concepts). 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.SUCCESS METRICS Reliable, efficient Dockerized builds delivered to partner satellites. Smooth operation and maintenance of NVIDIA/Xilinx dev kits for AI/ML use cases. Reduced latency and improved efficiency of ML models on embedded devices. Strong cross-team collaboration leading to faster turnaround on edge deployment milestones.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.EQUAL OPPORTUNITY EMPLOYMENT INFORMATION 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.

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