AI Research and Development Engineer

<h3>📋 Description</h3> • Are you passionate about transforming the world of realtime 3D rendering with AI? If so, we have an exciting opportunity for you. • Join Intel XeSS Research and Development team and be at the forefront of revolutionizing real-time 3D rendering with AI algorithms and neural rendering techniques. • As a part of our team, you'll delve deep into architecture, design, and development of optimized AI-based rendering software libraries, SDKs and algorithms for 3D game developers. • We are looking for a highly motivated senior AI Rendering Research and Development engineer with a strong AI and 3D graphics background, and expertise in neural rendering techniques with track record in delivering and leading successful AI software projects. • Working together with world-class AI and Graphics engineers, you will be developing deep learning solutions for 3D gaming, with focus on advanced techniques to provide dramatic performance and quality boost. <h3>🎯 Requirements</h3> • Bachelor's degree in Computer Science, Computer Engineering or Electrical Engineering or Physics or Mathematics or other related field with 6+ years of software development experience • Master's degree in Computer Science, Computer Engineering or Electrical Engineering or Physics or Mathematics or other related field with 4+ years of software development experience • PhD in Computer Science, Computer Engineering or Electrical Engineering or Physics or Mathematics or other related field with 2+ years software development experience. • 2+ years of experience with software following: Developing AI models leveraging modern model architectures and approaches dealing with 3D Graphics and/or Visual Computing domains. • Building custom AI training datasets and performing AI model training. • Strong knowledge and practical experience with PyTorch. • Solid Python programming skills. • Knowledge of broad range of AI algorithms and principles. • Realtime or physical-based 3D Graphics rendering. • Optimizing Deep Learning inference algorithms for GPU architectures. • Advanced Python and GPU programming (CUDA, OpenCL, DPC++) • Deep knowledge of GPU or Deep Learning Accelerator architectures. • Digital signal processing expertise.