Principal Embedded Systems Engineer (NVIDIA Jetson / Computer Vision)

Location: UK/EU / Onsite / Hybrid 3 out of 5 / Remote (only for exceptional candidate) 

Department: Core Engineering

Seniority Level: Principal / Lead

Industry: edge AI, embedded systems, dual-use systems (industrial IoT/ security/ defence /cyber tech)

About the Role

We’re hiring a Principal Embedded Systems Engineer to lead the design, optimization, and deployment of our embedded computer vision platform based on NVIDIA Jetson. This system integrates multiple cameras, edge AI models, and other peripherals in mission-critical environments. You will architect, build, and optimize the entire software stack — from Linux kernel to AI inference — and own key technical decisions around system performance, thermal optimization, and hardware compatibility.

Core Responsibilities

• Lead system architecture and embedded design across the Jetson platform (Orin/Nano/Xavier)
• Build and optimize Linux systems using Yocto Project and/or Buildroot
• Set up and tune ISP pipelines, handle multiple cameras via V4L2, and manage streaming pipelines via GStreamer
• Handle kernel configuration and performance optimization
• Lead system profiling and thermal optimization efforts across CPU, GPU, and memory
• Run hardware compatibility tests for selecting cameras, interfaces, power modules, etc.
• Deploy and run AI models on-device using tools like TensorRT, CUDA, and cuDNN
• Work with communication protocols like UART and MAVLink for integration with drones/UAVs
• Contribute to internal documentation, architecture specs, and build-test workflows
• Act as a proactive technical leader, challenging and owning solutions end-to-end

You’ll Thrive Here If You Have
Must-Have Technical Skills

• 5+ years working with embedded Linux systems (preferably with real deployments)
• Deep experience with Yocto Project or Buildroot
• Expertise in Jetson platforms (Nano, Orin NX, AGX) and JetPack SDK
• Strong C++ and Python skills for low-level and integration development
• Comfort with performance profiling tools and debugging embedded bottlenecks

• Familiarity with camera systems, ISP tuning, and Linux video stacks (V4L2)

   

Strong Plus

• Experience with GStreamer pipelines on embedded devices
• Hands-on with CUDA, TensorRT, cuDNN or other NVIDIA edge inference stacks
• Exposure to Balena, Mender, or other fleet/update management tools
• Understanding of UAV/drones systems, especially UART, MAVLink, or similar industrial communication protocols
• Prior exposure to robotics, or low-latency compute environments
• Experience integrating AI models on-device for real-time tasks

Collaboration & Mindset

• Excellent English and communication skills; ability to write specs and lead discussions
• Product ownership mindset — we’re looking for someone who owns decisions, not just executes tickets
• Ability to challenge solution architectures with well-structured, testable alternatives
• Collaborative mindset to work with AI, hardware, and firmware teams