We are now looking for a Software Engineer for TensorRT Inference! Would you like to make a big impact in Deep Learning by helping build a state-of-the-art inference framework for NVIDIA GPUs? Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. NVIDIA's GPUs run AI algorithms, simulating human intelligence, and act as the brains of computers, robots and self-driving cars that can perceive and understand the world. Increasingly known as "the AI computing company", NVIDIA wants you! Come, join our TensorRT Inference Architecture team, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly growing field.
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What you'll be doing:
- Develop components of TensorRT, NVIDIA's SDK for high-performance deep learning inference.
- Use C++, Python and CUDA to build graph parsers, optimizers, compute kernels and tools for effective deployment of trained deep learning models.
- Collaborate with teams of deep learning experts, GPU architects and DevOps engineers across diverse teams.
What we need to see:
- BS, MS, PhD or equivalent experience in Computer Science, Computer Engineering.
- 5+ years of software development experience
- Proficiency in C++
- Strong grasp of Machine Learning concepts.
- Excellent communication skills, and an aptitude for collaboration and teamwork.
Ways to stand out from the crowd:
- Experience developing System Software.
- Knowledge in shipping complex software packages.
- Prior experience in GPU kernel programming using CUDA or OpenCL.
- Experience in compiler development
- Background in working with TensorRT, PyTorch, TensorFlow, ONNX Runtime or other ML frameworks.
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