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Software Development Engineer– GPU Kernel & Community Development

Job in Markham, Ontario, Canada
Listing for: Advanced Micro Devices
Full Time position
Listed on 2026-03-01
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 CAD Yearly CAD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Overview

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. We focus on innovation, collaboration, and bold ideas to solve important challenges. Join us as we shape the future of AI and beyond. Together, we advance your career.

The Role

As a core member of the team, you will play a pivotal role in optimizing and developing deep learning frameworks for AMD GPUs. Your experience will be critical in enhancing GPU kernels, deep learning models, and training/inference performance across multi-GPU and multi-node systems. You will engage with internal GPU library teams and open-source maintainers to ensure seamless integration of optimizations, utilizing cutting-edge compiler technologies and advanced engineering principles to drive continuous improvement.

The Person

Skilled engineer with strong technical and analytical expertise in C++ development within Linux environments. The ideal candidate will thrive in both collaborative team settings and independent work, with the ability to define goals, manage development efforts, and deliver high-quality solutions. Strong problem-solving skills, a proactive approach, and a keen understanding of software engineering best practices are essential.

Key Responsibilities
  • Optimize Deep Learning Frameworks:
    Enhance and optimize frameworks like Tensor Flow and PyTorch for AMD GPUs in open-source repositories.
  • Develop GPU Kernels:
    Create and optimize GPU kernels to maximize performance for specific AI operations.
  • Develop & Optimize Models:
    Design and optimize deep learning models specifically for AMD GPU performance.
  • Collaborate with GPU Library Teams:
    Work closely with internal teams to analyze and improve training and inference performance on AMD GPUs.
  • Collaborate with Open-Source Maintainers:
    Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream.
  • Work in Distributed Computing Environments:
    Optimize deep learning performance on both scale-up (multi-GPU) and scale-out (multi-node) systems.
  • Utilize Cutting-Edge Compiler Tech:
    Leverage advanced compiler technologies to improve deep learning performance.
  • Optimize Deep Learning Pipeline:
    Enhance the full pipeline, including integrating graph compilers.
  • Software Engineering Best Practices:
    Apply sound engineering principles to ensure robust, maintainable solutions.
  • Outstanding written and verbal communication:
    Publish tutorials, technical blogs, and keep user guides, tutorials, and API references up to date.
  • Passion for open-source and AI acceleration:
    Community-oriented mindset.
Preferred Experience
  • GPU Kernel Development & Optimization:
    Experienced in designing and optimizing GPU kernels for deep learning on AMD GPUs using HIP, CUDA, and assembly (ASM). Strong knowledge of AMD architectures (GCN, RDNA) and low-level programming to maximize performance for AI operations, leveraging tools like Compute Kernel (CK), CUTLASS, and Triton for multi-GPU and multi-platform performance.
  • Deep Learning Integration:
    Experience in integrating optimized GPU performance into machine learning frameworks (e.g., PyTorch, vLLM) to accelerate model training and inference, with a focus on scaling and throughput.
  • Software Engineering:
    Skilled in Python and C++, with experience in debugging, performance tuning, and test design to ensure high-quality, maintainable software solutions.
  • Hands-on experience with modern inference engines such as vLLM, SGLang, or other large-scale or multi-modal inference runtimes.
  • Written and Verbal Communication:
    Outstanding communication skills and experienced in publishing technical tutorials and blogs, maintaining comprehensive and up-to-date user documentation, including user guides, tutorials, and API references.
  • Open-Source and AI Acceleration:
    Active contributor to open-source initiatives with a strong interest in AI acceleration technologies; values community collaboration and knowledge sharing to drive innovation and accessibility in AI development.
Academic Credentials
  • Bachelor’s and/or Master’s Degree in Computer…
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