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Principal Software Engineer – Team Lead (Edge AI LLM)
We are seeking a highly skilled Principal Software Engineer with expertise in GPU/TPU acceleration to join our team at Extreme Networks, Inc. The ideal candidate will have extensive hands-on experience in local Large Language Models (LLM) inference with embedded GPU/TPU architectures.
As a Principal Software Engineer specializing in Edge AI, you will play a crucial role in shaping the future Edge AI solution, leveraging the power of GPU/TPU acceleration and enterprise-grade, large-scale edge compute.
The successful candidate will combine technical excellence with effective leadership, creating a positive impact on both projects and team dynamics.
Key Responsibilities:- High-Level Design and Architecture
- 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, focusing on local Low Latency Model (LLM) inference.
- Implement and fine-tune low-latency model inference pipelines to meet real-time performance requirements.
- Collaborate with cross-functional teams to integrate AI inference solutions into edge computing platforms and applications.
- Collaborate with the GPU Hardware Design Team to design and optimize GPUs that power next-generation devices.
- Conduct performance profiling and optimization to maximize the efficiency of GPU/TPU acceleration for local LLM inference.
- Work on micro-architecture development, ensuring efficient execution of graphics, compute, and AI workloads within energy and area constraints.
- 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.
- 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.
- Develop project specifications, track progress, and control costs.
- Foster a positive work environment, encouraging professional growth and knowledge sharing.
- 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 (tensor, pipeline, data, sharded data parallelism) 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.
- 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.