About the job
The Software and AI (SAI) organization is seeking a highly skilled Software Development Engineer to contribute to the development and optimization of oneDNN, a complex, cross-platform, open-source performance library for deep learning applications (https://github.com/uxlfoundation/oneDNN). oneDNN is a critical and highly visible component of Intel’s AI strategy, powering industry-leading frameworks such as OpenVINO, TensorFlow, PyTorch, ONNX Runtime, and many others. This is a unique opportunity to work at the intersection of AI algorithms, low-level performance engineering, and cutting-edge Intel hardware, enabling state-of-the-art neural network performance across CPUs, integrated graphics, and discrete GPUs.
Responsibilities
Design, develop, and optimize new features and algorithms for oneDNN targeting Intel processors, Intel Processor Graphics, and Intel discrete GPUs.
Perform performance analysis and optimization to achieve best-in-class deep-learning inference and training throughput on current and next-generation Intel platforms.
Develop hardware-specific parallel algorithms, including multithreading, vectorization, and memory-layout optimizations.
Contribute to assembly-level programming and low-level performance tuning for Intel microarchitectures.
Collaborate with cross-functional teams across software engineering, architecture, and AI performance to ensure strong integration with Intel’s broader AI ecosystem.
Engage with the open-source community, participate in code reviews, and maintain high-quality coding and documentation standards.
Qualifications
Minimum
Master or PhD Mathematics, Physics, Computer Science or in a related field
5+ years of experience in the following areas:
C++
Algorithms and data structures, or Mathematical background
Low-level Performance Optimizations, preferably on GPUs
Preferred
3 years+ High-performance computing (HPC) applications development
1 year+ Machine learning and deep learning algorithms
1 year+ Agile software development environment
1 year+ Intel development tools.
Software libraries design and architecture
Background in Linear algebra solvers, matrix-vector operations, or Fast Fourier Transforms
Software development on Linux
GPU optimizations (OpenCL, CUDA, SYCL/DPC++, C for Metal or similar)
Parallel programming (OpenMP, TBB, or MPI)