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    Data Scientist - Bengaluru, India - Brillio

    Brillio
    Brillio Bengaluru, India

    Found in: Appcast Linkedin IN C2 - 20 hours ago

    Default job background
    Technology / Internet
    Description

    About Brillio:

    Based out of Silicon Valley, Brillio, a leading technology consulting and services company, continues to be at the forefront of data science innovation in 2023. Leveraging cutting-edge technology and advanced analytics, Brillio empowers businesses with data-driven insights to make informed decisions, optimize operations, and achieve remarkable outcomes. With a strong focus on machine learning, data analytics, and artificial intelligence, Brillio is helping organizations across diverse industries transform their data into a strategic asset. Their commitment to innovation and a client-centric approach positions Brillio as a trusted partner for unlocking the full potential of data science, ultimately driving growth and competitiveness.

    Brillio is seeking a highly skilled and experienced Senior Data Scientist with expertise in Natural Language Processing (NLP), Generative AI, Machine Learning (ML), and Deep Learning (DL). As a key member of our Data Science team, you will play a pivotal role in developing state-of-the-art solutions for our clients and driving innovation in the field.

    Must-Have

    • Ability to spearhead research initiatives in the field of Generative AI, particularly focusing on Large Language Models (LLMs).
    • Stay abreast of the latest advancements in machine learning, natural language processing, and generative modeling.
    • Conduct experiments to improve model architectures, training techniques, and generation capabilities.
    • Design and develop novel algorithms and architectures for enhancing the performance and efficiency of LLMs.
    • Optimize existing models for scalability, speed, and resource utilization.
    • Collaborate with cross-functional teams to integrate LLMs into production systems effectively.
    • Conduct thorough experimentation and validation to measure the performance of LLMs across various tasks and domains.
    • Proficiency in programming languages such as Python, along with expertise in deep learning frameworks like TensorFlow or PyTorch.
    • Proficient in deploying LLMs in production.
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