Internship - Robotics Hardware Acceleration Engineer (GPU)
Job description
•Dive into GPU acceleration for robotics during this paid internship. You will learn how to leverage parallel computing power using CUDA or OpenCL to speed up complex robotic tasks, working closely with our engineering team. Responsibilities may include: Assisting in the development and optimization of GPU kernels. Supporting the integration of GPU-accelerated code into robotics frameworks. Learning GPU programming tools and performance analysis techniques. Contributing to benchmarking and testing activities. Location: Vitoria-Gasteiz, Basque Country (Spain) - Hybrid work.
Preferred experiences
•Qualifications: Currently pursuing a Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical field. Strong programming skills, particularly in C++. Basic understanding of computer architecture and parallel computing concepts. Familiarity with GPU programming (CUDA or OpenCL) is a plus. Interest in robotics and high-performance computing. Analytical and problem-solving skills.
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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