Robotics Hardware Acceleration Engineer (FPGA)
Job description
•We are seeking a skilled Hardware Acceleration Engineer with a focus on FPGAs to accelerate robotic computations. You will work on designing, implementing, and verifying FPGA-based solutions to speed up tasks like perception, motion planning, and control within robotic systems, particularly using ROS 2. Key Responsibilities: Design and implement hardware accelerators using VHDL/Verilog for FPGAs (Xilinx preferred). Integrate FPGA designs with robotic software frameworks, particularly ROS 2. Develop high-level synthesis (HLS) designs to accelerate C/C++ code on FPGAs. Perform simulation, testing, and validation of FPGA designs. Collaborate with software engineers to define interfaces and optimize system performance. Stay updated with the latest FPGA technologies and tools. Location: Vitoria-Gasteiz, Basque Country (Spain) - Hybrid work.
Preferred experiences
•Minimum Qualifications: Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, or a related field. Minimum 3 years of experience in FPGA design and development (VHDL/Verilog). Experience with FPGA development tools (e.g., Xilinx Vivado/Vitis). Strong understanding of digital design principles and computer architecture. Experience with hardware/software co-design. Good programming skills in C/C++. Preferred Qualifications: Experience with High-Level Synthesis (HLS). Knowledge of robotics concepts and ROS/ROS 2. Experience with SoC FPGAs (e.g., Zynq UltraScale+). Familiarity with Linux and embedded systems development. Experience with verification methodologies (e.g., UVM).

Acceleration Robotics
Acceleration Robotics focuses on designing custom semiconductor building blocks, specifically FPGAs (Field-Programmable Gate Arrays) and SoCs (Systems-on-Chip), to accelerate robot computations. They create customized 'brains' for robots, aiming to significantly reduce response times and enable high-performance robotic systems. Their solutions involve hardware acceleration techniques tailored for robotics applications, particularly targeting the acceleration of ROS (Robot Operating System) computations and DDS network stacks, moving beyond traditional CPU-based approaches.
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