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    Job · 21251189

    BENGALURU · FULLTIME

    AI / ML Engineer

    Adagrad AI

    Adagrad AI

    Bengaluru · onsite · Posted 5d ago

    Sourced fromInstahyre
    Not disclosed6–10 yrsfulltimeBengaluru

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    Section · 01

    About this role

    We are seeking a skilled AI/ML Engineer with expertise in developing and deploying classical machine learning models for image/time series data and building agentic workflows with large language models.


    Responsibilities:

    • Preparing datasets from unstructured data in papers/books/internet by extracting images, text, and tables.
    • Developing knowledge graphs from unstructured data.
    • Applying data augmentation and synthetic data generation techniques to enhance model performance.
    • Develop agentic workflows around LLMs.
    • Preparing evaluation frameworks for LLMs for consistency.
    • Deploy large language models in on-premises environments.


    Requirements:

    • Strong understanding of deep learning concepts, including transformers, attention mechanisms, and transfer learning.
    • Developing and debugging machine learning models using Python and ML libraries (TensorFlow, PyTorch).
    • Expertise in graph neural networks is a plus.
    • Expertise in Large Language Models: Prompt engineering and agentic workflow are a plus.
    • 4+ years' experience; a mathematics, computer science, or electronics degree is required.

    Sourced from instahyre

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    Section · 02

    Skills

    PytorchTensorflowPythonMachine Learning

    Section · Company

    About Adagrad AI

    Adagrad AI

    Adagrad AI

    11-50

    employees

    2018

    8 years old

    Pune, Maharashtra

    India

    About

    Adagrad AI utilizes artificial intelligence to solve intricate design challenges, particularly in the self-driving technology sector.

    Industries

    Artificial Intelligence (AI)Computer VisionConsultingInformation TechnologyMachine LearningRetail

    Employee ratings

    14 reviews

    4.5/ 5

    Culture

    4.4

    Career growth

    4.4

    Work-life

    4.1

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