Senior GPU Performance Software Engineer
About The Position
The Software and AI (SAI) organization is seeking a highly skilled software engineer to contribute to the development and low-level optimization of oneDNN, a complex, cross-platform, open-source performance library that serves as the foundation for deep learning applications. This is a low-level software engineering and hardware-acceleration role focused on developing highly optimized math primitives, parallel algorithms, and GPU kernels that power industry-leading AI frameworks on Intel hardware. It does not involve building, training, or tuning machine learning models.
Requirements
- BSc, MSc, or PhD in Computer Science, Computer Engineering, Mathematics, Physics, or a highly technical related field
- 5+ years of professional software development experience with expert-level modern C++
- 2+ years of hands-on experience in programming and kernel optimization on GPUs (via SYCL/DPC++, OpenCL, CUDA, or HIP), or at least 5+ years of similar low-level performance optimization experience on CPUs
- Strong foundations in computer architecture, cache hierarchies, memory subsystems, and parallel programming paradigms (e.g., multi-threading, SIMD/vectorization)
Nice To Haves
- Experience developing high-performance math libraries (e.g., GEMM, convolution, reduction, or FFT kernels)
- Hands-on experience with GPU assembly-level tuning or compiler optimization
- Familiarity with parallel programming APIs such as OpenMP or oneTBB
- Basic understanding of deep learning primitives (e.g., forward/backward passes) to understand how library code is utilized by upstream frameworks
Responsibilities
- Develop high-performance GEMM, convolution, and attention kernels for AI workloads
- Design scalable JIT and codegen infrastructure for GPU kernel generation
- Implement fusion and memory-traffic optimizations to maximize hardware utilization
- Optimize mixed-precision and quantized execution paths (e.g., BF16, FP16, INT8, FP8, FP4, etc.)
- Build analytical and empirical performance models for kernel dispatch and tuning
- Profile and eliminate performance bottlenecks across oneDNN GPU primitives and runtime paths
- Co-design GPU primitives and kernel architectures for next-generation Intel GPUs
- Partner with hardware and compiler teams to shape future accelerator capabilities and software stacks
- Improve validation, benchmarking, and CI infrastructure for performance-critical GPU workloads
Benefits
- Competitive pay
- Stock bonuses
- Health benefits
- Retirement benefits
- Vacation benefits
- Stock programs
- Quarterly bonuses
- Robust healthcare
- Highly flexible hybrid/remote working options
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
