AI Software Development Engineer

Intel Corporation

. Optimize AI inference workloads, such as Large Language Models (LLMs), multimodal models, and emerging generative AI applications, for Intel GPUs .

Posted 11/5/2026full-timeFolsom • California • United StatesMid-LevelSenior💰 $149,750 - $275,580 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in optimizing AI inference workloads and performance-critical GPU kernels using C++ and parallel programming technologies. Proficient in collaborating across hardware and software teams to enhance AI frameworks and drive performance improvements.

Highest-signal resume keywords

C++ ProgrammingGPU Architecture UnderstandingPerformance Analysis and OptimizationAI Inference FrameworksNeural Network Optimization Techniques

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

C++SYCLVulkan ComputeOpenCLMLIRLLVMPerformance ProfilingDebuggingKernel TuningQuantization

Soft Skills

Problem-SolvingCollaboration

Tools & Technologies

OpenVINOPyTorchTensorRTONNX RuntimeAI Accelerators

Industry Keywords

AI Inference WorkloadsNeural Network ArchitecturesParallel Computing SystemsOpen-Source SoftwarePerformance Bottlenecks

Tech Stack

Tools & technologies

PyTorchC++

About the role

Key responsibilities & impact

Optimize AI inference workloads, such as Large Language Models (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 technologies like 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

Requirements

What you’ll need

Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, with 4+ years of relevant industry experience, OR Master's degree with 3+ years, OR Ph.D. with no prior professional experience
Strong proficiency in C++ programming, debugging, and problem-solving
Solid understanding of GPU architectures, Graphics Device Driver, 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
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 is a plus

Benefits

Comp & perks

Competitive pay
Stock bonuses
Health benefits
Retirement benefits
Vacation
Hybrid work model allowing employees to split time between working on-site and off-site