AI Embedded Software Architect

1 day ago


Pune, Maharashtra, India beBeeEmbeddedSoftwareEngineer Full time ₹ 1,07,47,000 - ₹ 1,91,95,000

We're looking for an Embedded Software Engineer to join our team. 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.

As an Embedded Software Engineer, you will be 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.

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.
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.
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.
EEO 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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