A

AMD

Designs chips for computers and AI systems

AI Framework Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeShanghai, ChinaNo salary listedIn-person

About the Job

Requirements

  • Strong technical and analytical expertise in C++ development within Linux environments.
  • Ability to define goals, manage development efforts, and deliver high-quality solutions.
  • Strong problem-solving skills and understanding of software engineering best practices.
  • Strong experience designing and optimizing GPU kernels for deep learning on AMD GPUs using HIP, CUDA, and assembly.
  • Strong knowledge of AMD architectures, including GCN and RDNA, and low-level programming for AI performance optimization using Compute Kernel (CK), CUTLASS, and Triton.
  • Experience integrating optimized GPU performance into machine-learning frameworks such as TensorFlow and PyTorch to accelerate training and inference, with a focus on scaling and throughput.
  • Expert skills in Python and C++, including debugging, performance tuning, and test design.
  • Experience running large-scale workloads on heterogeneous compute clusters and optimizing efficiency and scalability.
  • Understanding of compiler theory and tools such as LLVM and ROCm for kernel and system performance optimization.
  • Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
  • Professional experience in technical software development focused on GPU optimization, performance engineering, and framework development.

Responsibilities

  • Enhance and optimize deep-learning frameworks such as TensorFlow and PyTorch for AMD GPUs in open-source repositories.
  • Create and optimize GPU kernels to maximize performance for specific AI operations.
  • Design and optimize deep-learning models for AMD GPU performance.
  • Work with internal GPU library teams to analyze and improve training and inference performance on AMD GPUs.
  • Engage with framework maintainers to align code changes with requirements and integrate them upstream.
  • Optimize deep-learning performance on multi-GPU and multi-node systems.
  • Use compiler technologies to improve deep-learning performance.
  • Enhance the full deep-learning pipeline, including integrating graph compilers.
  • Apply sound engineering principles to produce robust, maintainable solutions.
  • Mentor junior team members through code reviews, knowledge sharing, and technical guidance.

About the Company

AMD

Designs chips for computers and AI systems

AMD designs processors, graphics chips and AI accelerators for computer makers, cloud operators and businesses that build electronic devices. Its Ryzen processors power personal computers, while EPYC processors handle work in data centers and Radeon chips render graphics. Instinct accelerators run AI models, paired with software that developers use to train models and put them into production. AMD sells chips and related computing systems through equipment makers, distributors and retail channels, and contracts with outside foundries to fabricate its semiconductor designs. It was founded in 1969 and has its headquarters in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1969

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