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    Machine Learning Engineer - bangalore, India - LeadSoc Technologies Pvt Ltd

    LeadSoc Technologies Pvt Ltd
    LeadSoc Technologies Pvt Ltd bangalore, India

    3 weeks ago

    Default job background
    Engineering / Architecture
    Description

    About Company :

    LeadSoC Technologies offers cutting edge Engineering Design services in VLSI and Embedded Systems. We have been growing rapidly since 2016 to meet the evolving needs of the Semiconductor, Automotive, Telecom and Consumer Electronics segments.

    Our Software practice works in areas spanning Firmware design, Hardware Abstraction, Kernel Space & User space design. We work on both bare metal and RTOS/Linux like platforms across x86, ARM, MIPS & Power PC architectures across multiple chipsets.

    We have an embedded Software COE with in-house Labs, powered by open-source tool chain equipped with variety of reference boards. This environment enables our engineers to play while they learn. It also creates an environment for the engineers to ideate / create reference Solutions, POC designs.

    Job Description:

    Education : BE/BTech/ME/MTech.

    Experience : 2-8 Years

    We are looking for Android AI/ML developer to join our engineering team to build AI workloads for profiling Memory & Storage power & performance bottlenecks.

    Candidate should possess strong knowledge in Android App development and/or ML frameworks for mobile Platforms (like TFLite, ONNX, SNPE/QNN etc).

    AI/ML Application Engineer Responsibilities:


    • Able to develop and/or customize AI models using ML frameworks like TFLite, PyTorch, ONNX, SNPE/QNN.


    • Develop Android applications by integrating the existing models from open-source.


    • Customize the AI models to run on different hardware models (GPU, DSP, NPU etc) available on the target platforms.

    Requirements:


    • At least 2yrs of real-time experience with development and/or performance optimization, quantization of AI/ML models on Edge platforms.


    • Able to customize the given models to different h/w delegates (GPU, DSP, NPU) as supported by the platform using any of the ML frameworks (TFLite, PyTorch, ONNX).


    • Hands-on with Android Application development for integrating the AI models using SDKs like Android Studio, Flutter.


    • Understanding of the Snapdragon Neural Processing Engine (SNPE), QNN frameworks is an additional advantage.


    • Decent understanding of Android Multimedia framework, Vulkan, OpenGL.

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