Nvidia Senior Computer Architect - Deep Learning 

United States, California 

121434497

What you'll be doing:

• As a member of our deep learning architecture team, you will contribute to features that help next-generation GPUs advance the state of AI.

• This position requires you to keep up with the latest DL research and collaborate with diverse teams (internal and external to NVIDIA), including DL researchers, hardware architects, and software engineers.

• Your day to day work will include analyzing the behavior of various deep learning methods, proposing new features to accelerate or enable various methods, and studying the benefits of the proposed features.

What we need to see:

• MS or PhD degree in computer science, computer architecture, electrical engineering or related field. Strong equivalent experience in several of the relevant areas listed below can substitute for an advanced degree.

• 3+ years of relevant experience in at least a few of the following relevant areas is required in your work history: Machine learning (with focus on Deep Neural Networks), including a solid understanding of DL fundamentals; Experience adapting and training DNNs for various tasks; Experience developing code for one or more of the DNN training frameworks (such as Caffe, TensorFlow or Torch): Numerical analysis, Performance analysis and optimization & Computer architecture.

• Programming fluency with C++ and ideally Python.

• Work experience with GPU computing (CUDA, OpenCL, OpenACC) and HPC (MPI, OpenMP) is a huge plus.

Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time. The era of AI has begun.