Canopy Artificial Intelligence is deploying computer vision infrastructure for construction site monitoring and needs an Embedded Linux Engineer in Dubai to physically commission two machines: an NVIDIA RTX PRO 6000 workstation and an NVIDIA Jetson AGX Thor, handing them back as remotely accessible, GPU-ready boxes.
About the Role – Hands-On GPU & Edge AI Commissioning
Core Focus: Unboxing, assembling, and bench-testing an RTX PRO 6000 workstation under sustained GPU load
Software Stack: Ubuntu Server 24.04, NVIDIA driver stack, CUDA toolkit, Docker, and NVIDIA Container Toolkit
Edge Device: Flashing an NVIDIA Jetson AGX Thor with the current JetPack release via SDK Manager
Networking & Security: Static IPs/DHCP, mesh VPN overlay (Tailscale/WireGuard), hardened SSH access
Application: Computer vision infrastructure for construction site monitoring
About the Role – Hands-On GPU & Edge AI Commissioning
Core Focus: Unboxing, assembling, and bench-testing an RTX PRO 6000 workstation under sustained GPU load
Software Stack: Ubuntu Server 24.04, NVIDIA driver stack, CUDA toolkit, Docker, and NVIDIA Container Toolkit
Edge Device: Flashing an NVIDIA Jetson AGX Thor with the current JetPack release via SDK Manager
Networking & Security: Static IPs/DHCP, mesh VPN overlay (Tailscale/WireGuard), hardened SSH access
Application: Computer vision infrastructure for construction site monitoring
Career Growth & Applied AI Infrastructure Impact
Strategic Location: Palm Jabal Ali, Dubai – hands-on physical commissioning work
Real Deliverables: Validated CUDA and TensorRT workloads running end-to-end before handover
Short, Focused Engagement: 2 weeks of on-site work plus 1 week of remote follow-up support
Career Growth: Build specialized, in-demand expertise in edge AI hardware commissioning and GPU infrastructure
Position Overview
This Embedded Linux Engineer role unboxes, assembles, and bench-tests an RTX PRO 6000 workstation with thermal validation under sustained GPU load, installs Ubuntu Server 24.04 with the full NVIDIA driver, CUDA, Docker, and container toolkit stack, and flashes an NVIDIA Jetson AGX Thor with the current JetPack release. You will configure networking with static IPs or a mesh VPN overlay, harden SSH access with key-only authentication and fail2ban, and validate the systems with working nvidia-smi/jtop reporting, sample CUDA and TensorRT workloads, and confirmed unattended reboot survival before handover.
Why This Role Matters: As Embedded Linux Engineer, you physically bring to life the GPU and edge AI hardware powering real computer vision infrastructure for construction site monitoring, apply hands-on expertise flashing NVIDIA Jetson devices and configuring workstation-class GPUs under real load conditions, harden systems with production-grade security practices including key-only SSH and fail2ban, deliver validated, remotely accessible infrastructure ready for immediate use, and complete a focused, well-defined engagement that showcases specialized, high-value edge AI commissioning skills.
Key Responsibilities
Workstation Assembly & Bench Testing
- Unbox, assemble, and bench-test an RTX PRO 6000 workstation (PSU, cooling, thermal validation under sustained GPU load)
- Install Ubuntu Server 24.04, NVIDIA driver stack, CUDA toolkit, Docker, and NVIDIA Container Toolkit
Edge Device Flashing
- Flash an NVIDIA Jetson AGX Thor with the current JetPack release via SDK Manager
Networking & Security Configuration
- Configure network settings: static IPs or DHCP reservations, port forwarding or mesh VPN overlay (Tailscale/WireGuard)
- Verify stable connectivity across both machines
- Configure hardened SSH access: key-only auth, no password login, no root login, fail2ban or equivalent
Validation & Handover
- Validate nvidia-smi and jtop reporting correctly on both machines
- Run a sample CUDA and TensorRT workload end-to-end
- Confirm unattended reboot survival before handover
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Qualifications & Requirements
Location Requirements
- Physically located in Dubai and able to work on-site at Palm Jabal Ali
Technical Experience
- Demonstrable experience flashing Jetson devices (Orin, Thor, or Xavier)
- Comfortable with Linux server administration, systemd, and networking fundamentals
- Prior work with NVIDIA driver/CUDA installs on workstation-class GPUs
Nice to Have
- TensorRT, GStreamer, or DeepStream exposure
- IP camera and RTSP/SRT streaming experience
- Rack, UPS, or edge-deployment background
About This Opportunity with Canopy Artificial Intelligence
Canopy Artificial Intelligence is deploying computer vision infrastructure for construction site monitoring, requiring hands-on physical commissioning of GPU workstation and edge AI hardware in Dubai. This engagement spans 2 weeks of on-site work at Palm Jabal Ali, with 1 week of remote follow-up support included as part of the fee, offering a focused, well-scoped opportunity for engineers with specialized NVIDIA hardware and Linux administration expertise.
Career Excellence: Apply specialized NVIDIA Jetson and GPU commissioning expertise to real computer vision infrastructure in Dubai.
Who Should Apply?
Dubai-Based Contractors: Available for a short, well-defined on-site engagement at Palm Jabal Ali
Jetson/Edge AI Specialists: With hands-on flashing experience across Orin, Thor, or Xavier devices
Linux System Administrators: Comfortable with systemd, networking, and hardened SSH configuration
GPU Workstation Engineers: Experienced installing NVIDIA drivers and CUDA on high-end workstations
Computer Vision Infrastructure Engineers: Familiar with TensorRT, DeepStream, or RTSP/SRT streaming
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