graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
graph level. - Document assumptions, APIs, and performance metrics for reproducibility. 3) Ideal Qualifications - Deep understanding of PyTorch internals (TensorIterator, dispatcher, autograd engine). - Strong background in C++ and template metaprogramming within PyTorch's ecosystem. - Experience authoring or extending PyTorch custom ops or backends. - Working knowledge of performance profiling tools and GPU/CPU interplay. - Strong written communication and ability to More ❯
