NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world.
Just as human creativity and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as “the AI computing company.”
Come join a team full of world-class computer scientists to work in its Compute Developer Technology team as an AI Developer Technology Engineer.

★What you'll be doing:

• You will work and develop state of the art techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures.
• Working directly with key application developers to understand the current and future problems they are solving, creating and optimizing core parallel algorithms and data structures to provide the best solutions using GPUs, through both library development and direct contribution to the applications.
• Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models.

★What we need to see:

• MS or PhD from a leading University in an engineering or Computer Science related discipline.
• Expertise in at least one of deep learning training framework such as Tensorflow, Pytorch, Caffe.
• Large model training experience on cluster/innovation domain (e.g., DL based rendering, etc.).
• Strong knowledge of C/C++, software design, programming techniques, and AI algorithms.
• Experience with parallel programming, ideally CUDA C/C++.
• Good communication and organization skills, with a logical approach to problem solving, time management, and task prioritization skills.

NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human creativity and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as “the AI computing company.”
Come join a team full of world-class computer scientists to work in its Compute Developer Technology team as a Developer Technology Engineer.

★What you'll be doing:

• You will work and develop state of the art techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures.
• You will provide the best AI solutions using GPUs working directly with key customers.
• Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models.

★What we need to see:

• MS or PhD from a leading University in an engineering or Computer Science related discipline.
• Strong knowledge of C/C++, software design, programming techniques, and AI algorithms.
• Experience with parallel computing skills, ideally CUDA/GPU/MPI/OpenMP/OpenCL.
• Good communication and organization skills, with a logical approach to problem solving, time management, and task prioritization skills.

We are now looking for a GPU / Deep Learning Architect.
Are you passionate about exploring computer architectures for deep learning? Do you like to work at the intersection of hardware and software? NVIDIA is seeking world class programmers and performance architects who love to squeeze out every cycle of performance from deep learning codes. In this role, you will write code that ships in our deep learning libraries, as well as guide the direction of our future GPU architectures. This position offers the opportunity to have real impact in a fast-moving, technology-focused company.

★What you'll be doing:

• Analyze the performance of various machine learning/DL algorithms on existing/new architectures.
• Identify bottlenecks and propose creative solutions to improve them.
• Prototype key deep learning and data analytics algorithms and applications.
• Understand and analyze the interplay of hardware and software architectures on future algorithms and applications.
• Add new capabilities to GPU architectures.

★What we need to see:

• MS or PhD in relevant discipline (CS, EE, Math).
• Track record of optimizing code for performance on CPUs or GPUs, including assembly or SIMD programming.
• Strong programming skills in C, C++, Perl, or Python.
• Familiarity with GPU computing (CUDA, OpenCL, OpenACC) and HPC (MPI, OpenMP).
• Strong background in computer architecture.
• Experience with matrix multiply and convolution algorithms.

★Ways to stand out from the crowd:

• Experience with parallel programming and CUDA/OpenCL.
• You are familiar with DL frameworks/fundamentals.
• Good communication and organizational skills.