该岗位需要onsite实习1年，有转正机会！ 我们特别需要以下关键领域的专业知识： 使用深度学习 (DL) 和人工智能 (AI) 技术实现游戏自动化，重点关注游戏行业的研究和应用。候选人应精通以下深度学习技术： • 深度强化学习 (DRL) • 卷积神经网络 (CNN) 和循环神经网络 (RNN) • 生成对抗网络 (GAN) 具备 AI 驱动机器人、游戏内移动自动化和玩家行为预测方面的经验或研究经验者优先考虑。 具备使用 AI 开发工具创建测试计划、开发测试用例和自动化测试用例的知识。

· Direction 1: Deep Learning Software Architect (Fast Kernals/TensorRT/ TensorRT-LLM/ Architecture) · Direction 2: GPU Graphics Performance Architect (Ray Tracing and Neural Rendering/ Real-time rendering/ SoC platform) · Direction 3: GPU Instruction Processor & Work Distributor Architect · Direction 4: System Software Engineer What you’ll be doing: · Design and verify next generation GPU architecture for computer graphics or high performance computing for cutting edge technology and features. · Develop production and core infrastructure software for key NVIDIA product line. · Optimize performance for gaming, ray tracing and deep learning applications at full stack from high level application, software stack to hardware architecture.

· Direction 1: Deep Learning Software Architect (Fast Kernals/TensorRT/ TensorRT-LLM/ Architecture) · Direction 2: GPU Graphics Performance Architect (Ray Tracing and Neural Rendering/ Real-time rendering/ SoC platform) · Direction 3: GPU Instruction Processor & Work Distributor Architect · Direction 4: System Software Engineer What you’ll be doing: · Design and verify next generation GPU architecture for computer graphics or high performance computing for cutting edge technology and features. · Develop production and core infrastructure software for key NVIDIA product line. · Optimize performance for gaming, ray tracing and deep learning applications at full stack from high level application, software stack to hardware architecture.

What you'll be doing: Performing in-depth analysis and optimization to ensure the best possible performance on current and/or next-generation NVIDIA GPUs. Understanding and analyzing the interplay of hardware and software architectures on core algorithms, programming models, and applications. Actively collaborating with the hardware design, software engineering, product, and research teams to guide the direction of accelerated computing. Diving into accelerated computing applications to facilitate software-hardware co-design. Write up and present your work by writing white papers, conference publications, official blog posts, patent applications, etc.

· Direction 1: Deep Learning Software Architect (Fast Kernals/TensorRT/ TensorRT-LLM/ Architecture) · Direction 2: GPU Graphics Performance Architect (Ray Tracing and Neural Rendering/ Real-time rendering/ SoC platform) · Direction 3: GPU Instruction Processor & Work Distributor Architect · Direction 4: System Software Engineer What you’ll be doing: · Design and verify next generation GPU architecture for computer graphics or high performance computing for cutting edge technology and features. · Develop production and core infrastructure software for key NVIDIA product line. · Optimize performance for gaming, ray tracing and deep learning applications at full stack from high level application, software stack to hardware architecture.