Principal Engineer – Team Lead (Edge AI LLM)
Description For Principal Engineer – Team Lead (Edge AI LLM)
Extreme Networks is seeking a talented Edge AI Principal Engineer with specialized expertise in GPU/TPU acceleration to join their team. This role focuses on shaping the future of Edge AI solutions, leveraging GPU/TPU acceleration and enterprise-grade, large-scale edge compute. The ideal candidate will have extensive hands-on experience in local Large Language Models (LLM) inference with embedded GPU/TPU architectures.
As a Principal Engineer specializing in Edge AI, you will play a crucial role in influencing the Edge AI strategy, making critical decisions on technical directions, and developing AI inference models for edge devices. You'll work on implementing low-latency model inference pipelines, collaborating with cross-functional teams, and optimizing performance for GPU/TPU acceleration.
Key responsibilities include high-level design and architecture, team leadership, and staying current with advancements in GPU/TPU technologies. You'll lead a team of engineers, oversee project planning and execution, and foster a positive work environment.
The ideal candidate should have a strong background in computer science or engineering, with 5+ years of hands-on experience in AI model development and deployment. Proficiency in Python, C++, and LLM frameworks is essential, along with extensive experience in GPU/TPU acceleration for AI inference.
This role offers an exciting opportunity to shape the future of AI at the edge and revolutionize industries with innovative edge AI solutions. Join Extreme Networks in pushing the boundaries of edge computing and GPU/TPU acceleration, particularly in local LLM inference, and be part of a dynamic and collaborative team.
Responsibilities For Principal Engineer – Team Lead (Edge AI LLM)
- Influence the Edge AI strategy by providing expert advice on design and architecture
- Make critical decisions regarding technical directions, scalability, and system performance
- Develop and optimize AI inference models for deployment on edge devices with embedded GPU/TPU accelerators
- Implement and fine-tune low-latency model inference pipelines
- Collaborate with cross-functional teams to integrate AI inference solutions
- Collaborate with the GPU Hardware Design Team
- Conduct performance profiling and optimization
- Work on micro-architecture development
- Stay current with advancements in GPU/TPU technologies and edge AI frameworks
- Provide technical expertise and support to project teams
- Lead and inspire a team of engineers
- Oversee project planning, execution, and delivery
- Manage all phases of technical projects
- Develop project specifications, track progress, and control costs
- Foster a positive work environment
Requirements For Principal Engineer – Team Lead (Edge AI LLM)
- 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 (e.g., vLLM, Text generation inference, OpenLLM, Ray Serve, and HuggingFace Transformers) 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, familiarity with NVIDIA Jatison, ARM Mali or relevant SoC configurations
- Knowledge of parallel computation, memory scheduling, and structural optimization
- Excellent problem-solving and analytical skills, with a passion for innovation and continuous learning
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