Job Title: Perception & Autonomous Systems Engineer
Reports to: Head of Engineering
Location: Bristol
Type: Full time - permanent
Role Overview
We are seeking a specialist Perception & Vision Systems Engineer to lead the development of high-performance imaging pipelines for our interceptor drone's seeker. This position focuses on the execution and optimisation of vision systems in real-time, high-stakes environments.
The role centers on the architecture of low-latency video pipelines - from MIPI/IP camera drivers through to CUDA -accelerated object detection and tracking. You will be responsible for ensuring our seeker can process high-resolution, high-FPS thermal and optical data, maintaining a stable and accurate state estimate that our guidance systems can rely on.
Key Responsibilities
- Vision Pipeline Architecture & Optimisation
- High-Throughput Processing: Design and optimise pipelines to handle large data packets (high-resolution video frames) at maximum FPS with minimal latency.
- Hardware Acceleration: Implement and tune vision algorithms using OpenCV, CUDA, and TensorRT to leverage the full power of NVIDIA Jetson edge hardware.
- GStreamer Experience: Build, debug, and maintain GStreamer pipelines for encoding, decoding, and frame manipulation across multiple camera modalities.
- Algorithm Development: Extend existing object detection and tracking systems, utilizing both deep learning and classical methods (e.g., ORB, SIFT, SURF) for robust target locking.
Sensor Integration & Hardware
- Camera Systems: Lead the integration of high-speed MIPI sensors, IP cameras, and
- Thermal (LWIR/MWIR) imaging systems.
- Driver Development: Troubleshoot and optimize camera drivers and V4L2 interfaces to ensure stable data acquisition under flight conditions.
- Coordinate Geometry: Manage spatial transformations and coordinate systems to bridge the gap between 2D image-space detections and 3D world-space tracking.
System Integration & Simulation
- ROS2 Integration: Maintain the perception-to-system interface via ROS2, ensuring vision outputs are efficiently consumed by the wider autonomous stack.
- Synthetic Data & Simulation: Utilize Unreal Engine, Unity, Gazebo or Other simulators to generate synthetic datasets and validate perception performance in virtual "edge case" scenarios.
- Testing & Validation: Implement rigorous unit and functional testing for perception modules, focusing on deterministic performance and edge-case reliability. Support field testing.
Required Experience
Industry Experience
- 3+ years in a specialised Vision Engineering or Perception role (UAV, Autonomous
- Vehicles, or Defence).
- 5–10 years professional engineering experience in C++ and Python, with a focus on
- real-time data processing.
Technical Expertise