AI/ML Embedded Systems Expert

2 days ago

Bareilly, Uttar Pradesh, India beBeeSoftware Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
AI/ML Embedded Software Engineer

We are seeking a highly skilled engineer to join our team in designing, implementing and optimizing embedded software solutions for AI/ML workloads.

The ideal candidate will have expertise in Linux environments, AI/ML optimization and testing on the edge, low-level engineering and containerization.

Key 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.
  • Develop pipelines for automated testing and deployment of embedded software builds.
  • Maintain clear documentation of configurations, workflows and deployment practices; support partner satellite companies in deploying our dockerized products.
  • Version control and collaboration: Git/GitHub, code review best practices and working in distributed development teams.
Complementary Skills:
  • Networking and protocols: Knowledge of embedded networking (TCP/IP, UDP, MQTT, gRPC) especially for low-bandwidth or intermittent links.
  • Security and 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 and automation: Bash, Python and Ansible (good to have) for automating builds, deployments and system monitoring.
  • Debugging and 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.

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