Hybrid AI Inference Engineer — Kernel & Performance

Intel; Hillsboro (OR); Hybrid; USD 189,000 - 315,000; Full time

Benefits offered by this job

Stock bonuses

Health benefits

Retirement plan

Paid vacation

Job summary

Intel is seeking a performance-driven AI Infrastructure Engineer to push LLM inference on next-gen Intel GPUs. You will profile, optimize, and write high-performance kernels, upstream improvements into vLLM and PyTorch, and collaborate with architecture teams to shape future GPU roadmaps.

You will contribute across the stack from kernel design to open-source integration, targeting state-of-the-art generative AI workloads and multi-node scale-out setups with a strong emphasis on performance and

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, AI/ML or related field with 4+ years experience, Masters with 3+ years, OR PhD.
• 3+ years of relevant software engineering experience in GPU computing, AI systems, or HPC.
• Proficiency in modern C++ and Python; comfortable reading and modifying complex systems-level code.

Responsibilities

• Drive Inference Performance: Own the end-to-end optimization pipeline for running state-of-the-art LLMs on Intel GPUs.
• Deep Stack Optimization: Profile, diagnose, and resolve cross-stack performance bottlenecks.
• Kernel Development and Integration: Design, write, and optimize custom high-performance kernels for attention, MoE, quantization, and operator fusions.
• Open Source Leadership: Upstream your architectural improvements and hardware backends directly into open-source repositories like vLLM, SGLang, and PyTorch, acting as a bridge between the hardware teams and the open-source community.
• Shape the Hardware Roadmap: Apply roofline analysis and systematic profiling to decompose bottlenecks. You will partner with our architecture and compiler teams to shape future GPU roadmaps based on real-world GenAI workload data.
• Show passion about AI infrastructure and performance optimization.

Skills

C++

Python

GPU computing

HPC

CPU/GPU architecture

LLM architectures

Open-source contributions

Kernel programming

Multi-node orchestration

AI coding agents

Education

Bachelor's degree in CS/related field

Master's degree in CS/related field

PhD

Tools

Triton

SYCL

CUDA/CUTLASS

PyTorch

vLLM

SGLang

Job description

Intel is seeking a performance-driven AI Infrastructure Engineer to push LLM inference on next-gen Intel GPUs. You will profile, optimize, and write high-performance kernels, upstream improvements into vLLM and PyTorch, and collaborate with architecture teams to shape future GPU roadmaps.

You will contribute across the stack from kernel design to open-source integration, targeting state-of-the-art generative AI workloads and multi-node scale-out setups with a strong emphasis on performance and