aic++llmmachine learningpytorchperformance optimizationgenerative aigpucompilerruntime systems
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Описание вакансии
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TL;DR
Senior AI Software Development Engineer (AI): Developing high-performance software to accelerate AI inference workloads, including Large Language Models and Generative AI, on Intel GPU platforms with an accent on compilers, runtimes, GPU kernels, and performance optimization. Focus on profiling compute-intensive workloads, designing scalable software solutions, influencing hardware-software co-design, and leading cross-functional technical initiatives.
Location: Hybrid work model in the United States, with on-site work at an assigned Intel site. Primary location: Folsom, California; additional locations: Santa Clara, California, and Hillsboro, Oregon.
Annual salary: $149,750–$275,580 USD.
Company
Intel develops hardware and software technologies for AI computing, including GPU platforms, compilers, runtimes, and AI frameworks.
What you will do
Lead optimization initiatives for AI inference workloads on Intel GPUs.
Define performance strategies across compilers, runtimes, GPU kernels, and AI frameworks.
Architect software solutions that improve scalability, efficiency, and performance.
Profile, benchmark, and analyze complex AI workloads to identify bottlenecks.
Influence hardware and software co-design through performance characterization and workload analysis.
Lead cross-functional initiatives and mentor engineers across architecture, compiler, framework, and runtime teams.
Requirements
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field with 5+ years of experience; or a master’s degree with 3+ years; or a PhD with 1+ years.
Experience in software development, AI systems, or performance engineering.
Professional experience with C++ software development and debugging.
Experience with performance analysis, profiling, and optimization of compute-intensive applications.
Experience with modern neural network architectures and their execution on hardware accelerators.
Ability to work in the United States under the role’s hybrid work model.
Nice to have
Experience with GPU architectures, AI accelerators, or parallel computing systems.
Experience optimizing production AI inference workloads.
Familiarity with llama.cpp, vLLM, OpenVINO, PyTorch, TensorRT, ONNX Runtime, or similar frameworks.
Experience with MLIR, LLVM, TVM, XLA, or related graph compilation technologies.
Experience with Vulkan Compute, OpenCL, SYCL, CUDA, HIP, quantization, kernel fusion, or memory optimization.
Culture & Benefits
Hybrid work with time split between an assigned Intel site and off-site work.
Competitive salary, stock bonuses, health benefits, retirement benefits, and vacation.
Collaboration with experts in AI, GPU architecture, compilers, runtimes, and systems software.
Opportunities to influence next-generation AI computing technologies and mentor engineers.
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