Senior Researcher - GPU Applications Architecture

Huawei Canada

Markham

On-site

CAD 90,000 - 120,000

Full time

14 days+

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Job summary

A leading technology firm is seeking a Senior Researcher - GPU Applications Architecture to conduct advanced analysis and drive GPU technology development. The ideal candidate will have in-depth knowledge in emerging AI applications, proficiency in GPU programming, and strong teamwork skills. This full-time role is positioned within a team dedicated to innovation in GPU architecture and applications.

Qualifications

  • Knowledge of physical AI, embodied AI, and 3DGS.
  • Experience in large-scale autopilot and robot simulation projects.
  • Proficiency in GPU performance analysis and tuning.

Responsibilities

  • Conduct analysis of technological trends for GPU computing.
  • Define hardware and system frameworks for GPU clusters.
  • Drive advancements in self-developed GPU technologies.

Skills

Emerging AI and GPU applications knowledge
AI-enhanced rendering technologies
GPU architecture and programming
Teamwork and communication skills

Tools

CUDA
OpenCL
Vulkan

Job description

Overview

Senior Researcher - GPU Applications Architecture at Huawei Canada. This is a permanent opening.

About the team

The Computing Data Application Acceleration Lab aims to create a leading global data analytics platform organized into three specialized teams using innovative programming technologies. This team focuses on full-stack innovations, including software-hardware co-design and optimizing data efficiency at both the storage and runtime layers. The team also develops next-generation GPU architecture for gaming, cloud rendering, VR/AR, and Metaverse applications. One of the goals of this lab is to enhance algorithm performance and training efficiency across industries, fostering long-term competitiveness.

About the job
  • Conduct in-depth analysis of physical AI, 3DGS, unmanned driving, and embodied AI application and technological trends. Thoroughly analyze key requirements for GPU computing architecture. Plan the environmental simulation and rendering platform based on self-developed GPU architecture, and provide development, training, and simulation capabilities for emerging applications.
  • Analyze GPU cluster systems. Define hardware architecture, system framework, and software architecture. Implement large-scale cluster intelligent solutions. Support the development and simulation of emerging applications such as physical AI, 3DGS, unmanned driving, embodied AI, and cloud rendering, ensuring industry-leading capability in environmental simulation and rendering.
  • Continuously drive technological competitive edge in space intelligence and propel the development of a self-developed GPU technology ecosystem.
Ideal candidate qualifications
  • In-depth knowledge about emerging AI and GPU applications, such as physical AI, embodied AI, 3DGS, World Models, etc. Experience in developing large-scale projects such as autopilot simulation and robot simulation is an asset.
  • In-depth knowledge about AI-enhanced rendering technologies/algorithms, such as DLSS and Neural Rendering. Experience with rendering engines (UE and Unity) is an asset.
  • Familiarity with AI chip architecture, computer architecture and operating systems, and distributed reasoning & training framework. Proven experience in designing system architectures.
  • Proficiency in GPU architecture and programming models, GPU programming languages including CUDA, OpenCL, and Vulkan, and APIs.
  • Expertise in GPU performance profiling and tuning. Ability to develop and utilize tools for thorough analysis and performance enhancement.
  • Strong teamwork and communication skills, enabling effective collaboration with team members to successfully execute projects.
Seniority level
  • Mid-Senior level
Employment type
  • Full-time
Job function
  • Research, Analyst, and Information Technology
  • Industries
  • Telecommunications
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