Robotics Hardware Acceleration Engineer (GPU)

undefined, Spain

•Full-time

3 years of experience• Hybrid

Tech

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Job description

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Join our team as a Hardware Acceleration Engineer specializing in GPUs. You will leverage the power of GPUs to accelerate computationally intensive robotic algorithms, such as computer vision, machine learning inference, and motion planning, primarily within the ROS 2 ecosystem. Key Responsibilities: Develop and optimize GPU kernels using CUDA and/or OpenCL for robotic applications. Integrate GPU-accelerated libraries and algorithms into ROS 2 nodes. Profile and benchmark software performance on various GPU architectures (NVIDIA preferred). Collaborate with robotics software engineers to identify acceleration opportunities. Stay current with advancements in GPU computing and parallel programming techniques. Contribute to the development of our hardware acceleration frameworks. Location: Vitoria-Gasteiz, Basque Country (Spain) - Hybrid work.

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Preferred experiences

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Minimum Qualifications: Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field. Minimum 3 years of experience in GPU programming (CUDA or OpenCL). Strong C++ programming skills. Understanding of parallel computing concepts and GPU architecture. Experience with performance optimization and profiling tools (e.g., Nsight Systems/Compute). Familiarity with Linux development environment. Preferred Qualifications: Experience with robotic systems and ROS/ROS 2. Knowledge of computer vision or machine learning algorithms. Experience with NVIDIA libraries (cuDNN, TensorRT, Isaac). Familiarity with other parallel programming models (e.g., OpenMP, SYCL). Experience with embedded GPU platforms (e.g., Jetson).

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.