Neural Rendering Research Inference Engineer – Advanced Graphics Programs

Technologies we use

Your responsibilities

• Work with ML researchers and engineers to translate neural network models and algorithms written in PyTorch/Onnx to efficient GPU shaders using languages such as HIP, Cuda, HLSL
• Design, implement and optimize high performance GPU kernels for ML operators.
• Work across research, hardware, driver and compiler teams to analyze and troubleshoot performance issues, provide solutions to improve rendering speed and ML workload efficiency.
• Stay current with latest advancements in GPU hardware, rendering techniques, graphics APIs and GPU accelerated ML.
• Contribute to the design and development of tools and methodologies for optimized shader integration to game engines.
• Document and share knowledge on best practices for GPU programming (both graphics and compute/ML) within the team.
• Participate in code reviews and provide constructive feedback to peers.

Our requirements

• Strong object-oriented programming background, C/C++ preferred
• Proven experience in developing and optimizing GPU kernels for machine learning workloads (eg:, using HIP, OpenCL, CUDA, HLSL )
• Ability to program in low level languages (x86 asm, SSE, ISA, Ptx, AMD assembly)
• Strong understanding of GPU architecture (compute cores, cache hierarchy, memory model), graphics APIs (DirectX, OpenGL, Vulkan, etc.), and shader programming.
• Solid understanding of common neural network operators, their mathematical foundations, and computational requirements.
• Experience with modern concurrent programming and threading APIs
• Experience with Windows, Linux operating system development
• Experience with software development processes and tools such as debuggers, source code control systems (GitHub) and profilers is a plus
• Understanding Machine Learning techniques and its application within graphics
• Effective communication and problem-solving skills
• Good interpersonal skills
• Undergrad degree required. Master's degree or PhD in Computer Science especially Graphics and/or Machine Learning, Computer Engineering, or equivalent preferred.

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