DescriptionAt Xilinx, we are leading the industry transformation to build an adaptable, intelligent world. ARE YOU bold, collaborative, and creative? At Xilinx, we hire and develop leaders and innovators who want to revolutionize the world of technology. We believe that by embracing diverse ideas, pushing boundaries, and working together as ONEXILINX, anything is possible.
Internships at the Xilinx Research Labs in Dublin, Ireland
Xilinx Research Labs is a small, diverse and dynamic part of Xilinx. Through customization and tailored solutions, we investigate how programmable logic and FPGAs can help make data centers faster, cheaper and greener by accelerating common applications and reducing the energy consumption of a given workload. Our team conducts cutting-edge research in topics such as machine learning, HPC and video processing to push the performance envelope of what’s possible with today’s devices and to help shape the next big thing in computing.
In particular, the team in Dublin is focused on deep neural networks, including training paradigms and techniques, hardware friendly novel topologies, quantization techniques, and custom hardware architectures that help support the enormous computational workloads associated with the roll-out of AI, even for energy-constrained compute environments. Fulfilling this goal requires top talent and thus we are looking to enrich our team with the finest engineers with bold, collaborative and creative personalities from top universities worldwide.
We seek enthusiastic engineers at preferably MSc or PhD level in Machine Learning, Electronic Engineering, Computer Science, and related disciplines. We look for the following skill sets in our candidates:
Understanding core concepts in neural networks and computer arithmetic
Fluent in Python, C++ and Linux shell scripting
Experience with Xilinx Vivado HLS, Vivado IP Integrator or SDAccel is a strong plus
Experience with common machine learning frameworks (Caffe, TensorFlow, PyTorch) is a strong plus
Strong communication skills, verbal and written