drjobs Edge AI Staff Engineer 9745

Edge AI Staff Engineer 9745

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1 Vacancy
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Job Location drjobs

Ontario, CA - USA

Monthly Salary drjobs

Not Disclosed

drjobs

Salary Not Disclosed

Vacancy

1 Vacancy

Job Description

Over 50000 customers globally trust our endtoend clouddriven networking solutions. They rely on our toprated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. With doubledigit growth year over year no provider is better positioned to deliver scalable outcomes than Extreme.

Inclusion is one of our core values and in our DNA. We are committed to fostering an inclusive workplace that embraces our differences and creates an atmosphere where all our employees thrive because of their differences not in spite of them.

Become part of Something big with Extreme! As a global networking leader learn why theres no better time to join the Extreme team.

Job Description:

We are seeking a talented Edge AI Staff Engineer with specialized expertise in GPU/TPU acceleration to join our team. The ideal candidate will have extensive handson experience in local Large Language Models (LLM) inference with embedded GPU/TPU architectures. As Staff 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

    • HighLevel 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 finetune lowlatency model inference pipelines to meet realtime performance requirements.
    • Collaborate with crossfunctional 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 nextgeneration devices.
    • Conduct performance profiling and optimization to maximize the efficiency of GPU/TPU acceleration for local LLM inference.
    • Work on microarchitecture development ensuring efficient 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.

    • Team Leadership:
    • Lead and inspire a team of engineers providing guidance setting goals and ensuring collaboration.
    • Oversee project planning 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.

Qualifications:

    • Bachelors degree in computer science Engineering or a related field; Masters degree preferred.
    • 5 years of handson 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 problemsolving and analytical skills with a passion for innovation and continuous learning.

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.


Required Experience:

Staff IC

Employment Type

Full-Time

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