AI/ML Developer

24 hours ago

Alleppey, Kerala, India beBeeEmbedded Full time ₹ 1,20,00,000 - ₹ 2,40,00,000
AI/ML Embedded Software Engineer Role

We are seeking a skilled embedded software developer to join our team. If you have experience in combining AI/ML with embedded systems, we would love to hear from you.

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 collaborate with cross-functional teams to develop cutting-edge technology that powers our edge intelligence solutions in space. As an Embedded Software Engineer, you will have the opportunity to work with modern embedded platforms, shape the future of real-time satellite intelligence, and make a meaningful impact on our mission to reimagine how satellites process and deliver intelligence from orbit.

To succeed in this role, you should have a strong background in C, C++, and Python, as well as deep knowledge of Linux (system internals, drivers, kernel tuning). Proven experience with Docker and containerized workflows is also essential. If you have experience with NVIDIA Jetson, CUDA, TensorRT, and Xilinx Vitis AI / OpenCL, that's a plus

Key Responsibilities:
  • Design, implement, and optimize embedded software solutions for AI/ML workloads on NVIDIA, Xilinx, and Microchip platforms.
  • Build and maintain Linux-based environments, write integration libraries, and enable containerized deployment of applications on constrained edge devices.
  • Collaborate with cross-functional teams to develop cutting-edge technology that powers our edge intelligence solutions in space.
Requirements:
  • Strong background in C, C++, and Python programming languages.
  • Deep knowledge of Linux system internals, drivers, and kernel tuning.
  • Proven experience with Docker and containerized workflows.
  • Familiarity with NVIDIA Jetson, CUDA, TensorRT, and Xilinx Vitis AI / OpenCL.
Benefits:
  • Reliable, efficient Dockerized builds delivered to partner satellites.
  • Smoother 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.

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