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انتهت صلاحية هذه الوظيفة في 19/07/2026. لم تعد تقبل الطلبات.

Back-End Engineer (Edge AI/CV Orchestration)

RIME Platform · Riyad

Mid 🇬🇧 English
Python NVIDIA Jetson JetPack SDK Linux Docker containerd K3s MicroK8s NVIDIA DeepStream TensorRT Triton Inference Server C++ Go Computer vision AWS IoT Greengrass Azure IoT Edge Balena APIs Microservices

وصف الوظيفة

About the role

Rime is looking for an experienced Edge AI/CV Orchestration Engineer to enhance and scale the core engine that manages AI workloads on resource‑constrained edge devices. You will bridge backend infrastructure and physical hardware, ensuring efficient, reliable operation of devices such as the NVIDIA Jetson Orin Nano.

Key responsibilities

  • Design, develop, and optimize new features for the Python‑based orchestration engine.
  • Implement robust resource allocation, task scheduling, and priority management across a fleet of edge devices.
  • Profile and fine‑tune AI/CV pipelines on Jetson platforms, addressing performance bottlenecks in the Linux environment.
  • Maintain and evolve APIs and microservices that support the orchestration layer.
  • Collaborate with hardware and AI teams to integrate NVIDIA stack components (DeepStream, TensorRT, Triton).

Required profile

  • 3‑5+ years of experience in backend development, systems programming, or DevOps, preferably with distributed or embedded systems.
  • Strong background in Linux system administration, performance tuning, and scripting.
  • Proven ability to work with NVIDIA Jetson hardware and the JetPack SDK.
  • Experience designing, building, and maintaining APIs and microservices.

Required skills

  • Python (including asyncio and system‑level scripting)
  • NVIDIA Jetson platforms (Orin Nano, Xavier NX, AGX) and JetPack SDK
  • Linux operating system, shell scripting, networking, performance tools
  • Docker and container runtimes (containerd)
  • Edge‑focused Kubernetes distributions (K3s, MicroK8s)
  • NVIDIA DeepStream, TensorRT, Triton Inference Server (preferred)
  • Computer vision / machine‑learning model deployment concepts
  • C++ or Go for performance‑critical components (optional)
  • IoT fleet management tools such as AWS IoT Greengrass, Azure IoT Edge, Balena (optional)

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