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    MLOps Engineer - Pune, India - TWise

    TWise
    TWise Pune, India

    20 hours ago

    Default job background
    permanent Technology / Internet
    Description

    Responsibilities :

    Lead Machine Learning Projects:
    Take ownership of end-to-end machine learning projects, from problem definition and data collection to model development and deployment.

    Team Leadership:
    Mentor and guide a team of machine learning engineers, providing technical expertise and leadership to ensure project success.

    Algorithm Development:

    Develop and optimize machine learning algorithms and models, leveraging techniques such as deep learning, natural language processing, computer vision, and reinforcement learning.


    Data Preparation:
    Clean, pre-process, and transform large datasets to create high-quality training data for machine learning models.

    Model Evaluation:
    Implement rigorous testing and validation procedures to ensure the performance, accuracy, and scalability of machine learning models.

    Deployment and Integration:
    Collaborate with cross-functional teams to deploy machine learning models into production environments and integrate them with existing systems.

    Research and Innovation:

    Stay up-to-date with the latest advancements in machine learning and AI research, and apply innovative solutions to business problems.


    Documentation:
    Maintain detailed documentation of models, algorithms, and processes to facilitate knowledge sharing within the team and organization.

    Collaboration:

    Collaborate with data scientists, data engineers, and other stakeholders to drive the adoption of machine learning across the organization.


    Qualifications :

    • Minimum of 4 years of hands-on experience in machine learning, deep learning, and artificial intelligence.
    • Strong programming skills in languages such as Advanced Python
    • Proficiency in data pre-processing, feature engineering, and model evaluation.
    • Proven experience ML Flow, CICD, Docker, Kubernetes, Continuous Integration, Deployment, Git actions, ML Studio, Pipeline Azure Databricks, Azure ML Studio, DevOps, Terraform
    • Statistics and machine learning knowledge
    • Azure ML is must and good to go
    • Standardize and streamline prototype machine learning code
    • Building MLOps pipelines. Building to serve data and models


    If you are a seasoned machine learning engineer with a passion dashboard for solving complex problems using cutting-edge technologies, we encourage you to apply.

    Join our dynamic team and play a pivotal role in advancing our AI and ML initiatives.
    )

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