Senior System Software Engineer, Deep Learning

• Develop solutions around NVIDIA GPU and Deep learning accelerators to realize DNNs for ADAS Systems. • Optimize DNNs for the GPU and other hardware accelerators like DLA using CUDA/TensorRT. • Improve DNN architectures using ML algorithms on NVIDIA GPUs or DLAs. • Conduct benchmarking and evaluation activities to continuously improve inference latency, accuracy and power consumption of DNNs. • Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas to improve NVIDIA's automotive DNNs. • Responsible for the technical relationship and assisting the automotive customer in building creative solutions based on NVIDIA technology. • Collaborate with engineering teams in our US, APAC, India and Europe locations.

• BS/MS or higher degree in Computer Science, Computer Engineering or Electrical Engineering. • Experience in developing or using deep learning frameworks (e.g. TensorFlow, Keras, PyTorch, Caffe, ONNX, etc.). • 5+ years of experience in optimizing DNN Layers for GPU or other DSPs. • Proficiency in C and C++ and Data Structures. • Strong OS fundamentals and knowledge of CPU/GPU architecture. • Familiar with state-of-the-art CNN/LSTM/Transformers architecture.

• Strong analytical and problem solving skills, with good attention to details. • Background with NVIDIA software libraries such as CUDA and TensorRT. • Experience in automotive development processes like ASPICE or ISO26262. • Excellent communication and organization skills, good time management and task prioritization. • Open source project ownership or contribution, GitHub repositories, guiding and/or mentoring experience. • Understanding of the DRIVE or NVIDIA GPU hardware.

• For more details, please refer to the company website.