Edge Systems Engineering Intern

Role Overview

InSiSo Technologies is looking for an Edge Systems Engineering Intern to work on InSiSoNet, a proprietary vision AI architecture. This is a working assessment designed as a fast-track to full-time employment. The role involves deploying vision applications onto industrial controllers in real production environments and requires immediate relocation to Bengaluru for on-site client deployment work.

Responsibilities

• Package and deploy vision applications as snaps onto ctrlX CORE controllers.
• Build and maintain the ctrlX AddOn build environment and own the deployment pipeline.
• Handle device configuration, networking, Data Layer integration, and actuation signal output.
• Integrate AI accelerators like Hailo-8 and industrial cameras into the runtime.
• Benchmark end-to-end latency on target hardware.
• Implement fail-safe behavior for low-confidence and inference-failure states.
• Perform on-site debugging and field fixes at client locations.
• Write comprehensive deployment documentation.

Requirements

• Strong Linux fundamentals (systemd, permissions, networking, filesystem).
• Experience or fast learning ability with Snap packaging (snapcraft).
• Proficiency with Containers (Docker), build systems (CMake, Make), and cross-compilation.
• Strong programming skills in Python and C++.
• Understanding of networking basics: TCP/IP, ports, and firewalls.
• Ability to relocate to Bengaluru immediately for on-site work.
• Methodical debugging skills for hardware environments.

Skills

• Linux
• Python
• C++
• Docker
• Snapcraft

Nice to Have

• ctrlX AUTOMATION, ctrlX WORKS, or industrial PLC platforms (Beckhoff, Siemens).
• Embedded Linux on ARM, Yocto, or Buildroot.
• ROS / ROS2.
• GStreamer, V4L2, or video pipeline work.
• Industrial camera interfaces (GigE Vision, USB3 Vision, MIPI CSI).
• Hardware accelerator toolchains (Hailo, OpenVINO, TensorRT).