大模型算法实习生（模型量化/低比特训练推理）Jan - Jun 2026 Job Listing at AMD in Beijing, Beijing (Job ID 70556-en-us)

Description

WHAT YOU DO AT AMD CHANGES EVERYTHING

We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world's most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. 

AMD together we advance_

职位描述

1. 研究和开发大模型优化算法，包括但不限于模型（如CNN、LLM、Vision LLM等）的量化、剪枝、蒸馏、压缩等算法设计与实现，提高训练和推理性能
2. 分析模型和数据类型特点，制定对应的推理优化与量化策略，鼓励创新和论文发表；
3. 关注低比特数据类型的模型训练，分析和解决精度与性能问题
4. 跟踪AI领域最新研究成果和技术动态（特别是大模型量化和推理加速技术），评估其在实际产品中的应用潜力和落地价值，提出改进和创新的想法，推动团队的技术发展。

职位要求

1. 扎实的C/C++或者Python基础，熟悉至少一种深度学习框架（如PyTorch、TensorFlow、JAX等）；
2. 对AI算法和应用有深刻的理解，熟练掌握机器学习、深度学习、强化学习等理论知识，具备模型训练与部署的完整开发经验；或者有模型量化/剪枝/蒸馏/压缩相关科研或项目经验；或了解Flash Attention/Memory Efficient Attention等kernel的实现方法
3. 有下列实际项目经验（至少一项）：模型量化工具开发、模型推理（加速）框架开发、GPU/TPU/NPU算子开发、AI处理器设计等;
4. 对 AI 模型压缩有深入理解，至少具备以下一项实际开发经验：
   1. 量化工具链开发（如 PTQ、QAT、混合精度推理等）；
   2. 推理加速框架优化（如 ONNX Runtime、TensorRT、TVM、XLA 等）；
   3. GPU/TPU/NPU 等异构硬件的算子开发与性能调优；
   4. AI 芯片架构设计与软件协同开发；
5. 具备良好的科研能力或工程创新能力，在模型压缩/推理优化领域的国际顶会（如 NeurIPS、ICLR、CVPR、MLSys 等）有论文发表者优先；
6. 熟悉Triton/Cutlass者优先；
7. 有大模型分布式训练经验者优先。

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Benefits offered are described:  AMD benefits at a glance.

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law.   We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.