Principal Engineer: Xess and Neural Graphics

Intel Intel · Semiconductors · Oregon, Hillsboro, United States

Principal Engineer to drive Intel's XeSS and related AI-based graphics technologies, impacting XeSS Super Resolution, Frame Generation, Neural Rendering, and next-gen AI rendering. The role involves shaping technical direction, driving execution across research, software, hardware, validation, and ecosystem teams, and bringing AI graphics technologies from concept to product. Responsibilities include end-to-end development across model design, datasets, training, visual quality, performance optimization, and product integration, as well as guiding the application of modern AI model architectures to future graphics workloads.

What you'd actually do

  1. Drive Intel's XeSS and related AI-based graphics technologies for Client Graphics, with direct impact across XeSS Super Resolution, XeSS Frame Generation, Neural Rendering, and next-generation AI rendering capabilities.
  2. Help shape technical direction, drive execution across teams, and contribute to the future of AI-based graphics at Intel.
  3. Work across research, software, hardware architecture, validation, and ecosystem teams to bring new AI graphics technologies from concept to product.
  4. Play a key role in end-to-end development across model design, datasets, training, visual quality, performance optimization, and product integration.
  5. Help guide how modern AI model architectures are applied to future graphics workloads.

Skills

Required

  • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or related field, with 12+ years of experience, or Master's degree with 10+ years of experience.
  • Strong expertise in AI/ML for real-time graphics, imaging, or video, such as super resolution, frame generation, denoising, reconstruction, optical flow, or related AI rendering workloads.
  • Proven experience driving AI technology from research to shipped product, including model architecture, datasets, training, evaluation, optimization, and deployment.
  • Strong understanding of GPU architecture, performance, memory, latency, and hardware-aware optimization.
  • Demonstrated leadership across cross-functional technical teams spanning research, software, and hardware.

Nice to have

  • Experience with XeSS, Neural Rendering, or adjacent AI-based graphics technologies.
  • Good understanding of modern AI model architectures, such as LLMs, Vision Transformers, Diffusion, and related architectures.
  • Experience with high-performance GPU compute, inference kernels, or production AI deployment.
  • Experience with dataset capture, processing, and training infrastructure for graphics AI models.
  • Experience with SDK, API, or cross-platform AI productization.
  • Experience influencing future GPU, NPU, or accelerator features based on AI workload analysis.

What the JD emphasized

  • Proven experience driving AI technology from research to shipped product
  • Strong understanding of GPU architecture, performance, memory, latency, and hardware-aware optimization
  • Experience with high-performance GPU compute, inference kernels, or production AI deployment

Other signals

  • AI-based graphics technologies
  • end-to-end development
  • model design, datasets, training, visual quality, performance optimization, and product integration
  • modern AI model architectures applied to future graphics workloads