We are partnering with an innovative Earth Observation company developing next-generation satellite imaging payloads. They are seeking an experienced FPGA Design Engineer to take ownership of high-performance image acquisition and processing systems, working across the full data path from sensor interfaces through to onboard processing and memory architectures.

This is a hands-on role focused on designing robust, high-throughput FPGA solutions for demanding imaging applications, collaborating closely with hardware, software, and systems teams in an agile development environment.

Key Responsibilities

• Develop and optimise VHDL for Xilinx 7-Series, UltraScale+, and Versal device.
• Design high-speed interfaces including PCIe, Ethernet, MIPI CSI-2, and SerDes-based communication.
• Architect and implement high-bandwidth data paths using AXI protocols, DMA, and memory interface.
• Support AI and image processing acceleration on FPGA platform.
• Configure and optimise DDR4/LPDDR4 memory subsystem.
• Perform timing analysis, timing closure, and multi-clock domain design.
• Debug and validate hardware using simulation, hardware-in-the-loop testing, and FPGA debugging tool.
• Contribute to technical documentation, processes, and product development best practice.
• Drive continuous improvement and contribute innovative ideas to future product development.

Requirements:

• Degree in Electronics Engineering, Telecommunications, Computer Engineering, or a related discipline.
• Strong commercial experience developing FPGA designs in VHDL.
• Extensive experience with Xilinx FPGA architectures and toolchains, including Vivado and Vitis.
• Strong understanding of AXI-based architectures, IP integration, and high-speed digital design.
• Experience with simulation, verification, and testbench development.
• Proficiency with Tcl and/or Python scripting.

Desirable Experience:

• Xilinx Versal AI Engine and NoC architectures.
• Vitis HLS and hardware acceleration workflows.
• Space, satellite, or other high-reliability embedded systems environments.
• Radiation-tolerant design and SEU mitigation techniques.
• Image processing, computer vision, or AI acceleration on FPGA platforms.