What are the responsibilities and job description for the Neural Rendering Research Inference Engineer – Advanced Graphics Programs position at Advanced Micro Devices, Inc?
WHAT YOU DO AT AMD CHANGES EVERYTHING
At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
THE ROLE:
- AMD is looking for a strategic research inference engineer who is passionate about improving the performance of key ML applications by designing, implementing and optimizing high performance GPU kernels for ML operators. You will be a member of a core team working with incredibly talented ML researchers who are path finding new technologies in real time neural graphics, inverse rendering and other ML accelerated opportunities.
KEY 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.
PREFERRED EXPERIENCE:
- 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
ACADEMIC CREDENTIALS:
- 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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