Nvidia is hiring a
Senior System Software Engineer - AI
NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s motivated by great technology and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. NVIDIA is at the forefront of generative AI models, from language to images. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work.
We are looking for a passionate, extraordinary engineer for the Enterprise Workstation team to develop software that integrates many pioneering AI libraries like TensorrRT and cuDNN. Come join the team and see how you can make a lasting impact on the world.
What you will be doing:
Design and use your coding expertise to optimize and productize NVIDIA's AI models. This will involve building a strong coding & and deployment pipeline for the AI models.
Write effective, maintainable and well-tested code
Collaborate closely with the architecture, research, libraries and tools teams at NVIDIA to achieve ideal results for AI problems at hand
What we need to see:
BE / MS in Computer Science or related field
7+ years of relevant work experience. 3+ years in Machine Learning frameworks such as PyTorch, Tensorflow, ONNX Runtime, and TensorRT
Strong knowledge of C/C++, python and firsthand experience with parallel programming, ideally CUDA C/C++.
Understanding of modern techniques in Machine Learning, Deep Neural Networks and Generative AI with meaningful contributions to major open-source projects will be a plus
Excellent communication and interpersonal skills along with the ability to work in a dynamic and distributed team.
Strong computer science fundamentals - algorithms and data structures, computational complexity, parallel computing, system software.
Ways to stand out from the crowd:
Exposure to container technology like dockers and cloud based deployments for AI models
Consistent track record of delivering end to end products with geographically distributed teams in multinational product companies
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