Senior Software Engineer

4 weeks ago

Toronto, Ontario, Canada Extreme Networks Full time
Job Title: Senior/Staff/Principal Engineer

We are seeking a highly skilled Senior/Staff/Principal Engineer to join our team and contribute to the development of cutting-edge Edge AI solutions. The ideal candidate will have extensive experience in GPU/TPU acceleration and local Large Language Models (LLM) inference.

Key Responsibilities:
  • Design and develop high-performance AI inference models for deployment on edge devices with embedded GPU/TPU accelerators.
  • Collaborate with cross-functional teams to integrate AI inference solutions into edge computing platforms and applications.
  • Conduct performance profiling and optimization to maximize the efficiency of GPU/TPU acceleration for local LLM inference.
  • Stay current with advancements in GPU/TPU technologies and edge AI frameworks, incorporating them into solution designs as appropriate.
  • Provide technical expertise and support to project teams, ensuring successful implementation and deployment of edge AI solutions.
Team Leadership:
  • Lead and inspire a team of engineers, providing guidance, setting goals, and ensuring collaboration.
  • Oversee project planning, execution, and delivery, ensuring alignment with business objectives.
  • Manage all phases of technical projects, from conception to completion.
  • Foster a positive work environment, encouraging professional growth and knowledge sharing.
Qualifications:
  • Bachelor's degree in computer science, engineering, or a related field; Master's degree preferred.
  • 5+ years of hands-on experience in AI model development and deployment, with a focus on edge computing and local LLM inference.
  • Strong programming skills in languages such as Python and C++.
  • Proficiency in LLM frameworks and deep learning libraries.
  • Extensive experience with GPU/TPU acceleration for AI inference, including optimization techniques and performance tuning.
  • Hands-on experience with one or more GPU frameworks: CUDA, Vulkan, OpenCL.
  • Deep knowledge of GPU memory layout and familiarity with NVIDIA Jatison, ARM Mali, or relevant SoC configurations.
  • Knowledge of parallel computation, memory scheduling, and structural optimization.
Additional Skills (Preferred):
  • Experience with edge device hardware and software integration.
  • Familiarity with edge computing architectures and IoT platforms.
  • Experience with edge AI applications in domains such as robotics, autonomous vehicles, or industrial automation.

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