AI Software Development Engineer

Intel Corporation•Santa Clara, CA

22h•$149,750 - $275,580•Hybrid

About The Position

Intel is seeking an AI Software Development Engineer to optimize AI inference workloads for Intel GPUs. The role works across the AI software stack, improving performance-critical GPU kernels, graph compilation flows, and inference runtimes to enhance the efficiency and scalability of modern AI workloads. As part of Intel's Software Group, the engineer will contribute to software solutions, tools, frameworks, and optimizations that enable Intel AI products and support developers. The work includes optimizing LLM, multimodal, and generative AI applications, analyzing performance across software layers, and collaborating with hardware, driver, compiler, and framework teams on hardware/software co-optimization. The position is eligible for Intel's hybrid work model, with time split between the assigned Intel site and off-site.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, with 4 or more years of relevant industry experience; or a master's degree with 3 or more years of relevant experience; or a Ph.D. with no prior professional experience.
Strong proficiency in C++ programming, debugging, and problem-solving.
Solid understanding of GPU architectures, graphics device drivers, firmware, AI accelerators, or parallel computing systems.
Experience with performance analysis, profiling, and optimization for compute-intensive applications.
Hands-on experience with modern neural network architectures and their execution on hardware accelerators.

Nice To Haves

Experience optimizing end-to-end AI inference workloads in production environments.
Familiarity with AI inference frameworks such as OpenVINO, PyTorch, TensorRT, ONNX Runtime, or similar technologies.
Knowledge of neural network optimization techniques, including quantization, kernel fusion, and memory optimization.
Experience across multiple layers of the AI software stack, including inference runtimes, graph compilers, and GPU kernels.
Experience contributing to open-source software projects.

Responsibilities

Optimize AI inference workloads, including LLMs, multimodal models, and emerging generative AI applications, for Intel GPUs.
Design, develop, and tune performance-critical GPU kernels and runtime components using C++, SYCL, Vulkan Compute, OpenCL, or similar parallel programming technologies.
Develop and optimize graph compilation flows and compiler passes using MLIR, LLVM, or related frameworks.
Identify and resolve performance bottlenecks across compiler, runtime, framework, and kernel layers.
Profile, benchmark, and analyze AI workloads to validate performance improvements and guide optimization strategies.
Collaborate with hardware, driver, compiler, and framework teams to drive hardware/software co-optimization.
Contribute to and optimize open-source AI inference frameworks such as OpenVINO, llama.cpp, vLLM, PyTorch, or related ecosystems.