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    MLOPS Engineer - Pune, India - LTIMindtree

    LTIMindtree
    LTIMindtree Pune, India

    17 hours ago

    LTIMindtree background
    Description

    Role:
    MLOps Engineer

    Total Experience: 6 years

    Job Location- Pune
    Role Description

    Looking for an experienced and motivated GCP evangelist who will work as MLOps Engineer and will be designing, developing, and maintaining the infrastructure and workflows necessary to support the deployment and scaling of multiple concurrent machine learning services.

    The ideal candidate for this role should has expertise in MLOps, automation, optimisation, and cloud infrastructure which will be essential in scaling our machine learning capabilities
    Job Description


    • Overall, more than 8 years of experience working as MLOps engineer
    • Design and implement cloud solutions, build MLOps on cloud (AWS, Azure, or GCP)
    • Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Circle CI, Airflow or similar tools.
    • Communicate with a team of data scientists, data engineers and architect, document the processes.
    • Knowledgeable on agile practices.

    ML Model Deployment:
    Assist in deploying machine learning models into production environments.


    • AI ML pipeline and model Monitoring: Contribute to the monitoring and maintenance of model performance and infrastructure health

    Automation:
    Participate in the development and maintenance of automated MLOps pipelines

    Collaboration:
    Collaborate with cross-functional teams to integrate machine learning models into production systems.

    Documentation:
    Maintain documentation of MLOps processes and procedures.


    • Work closely with members of technology teams in the development, and implementation of Enterprise AI platform

    Problem Solving:
    Assist in troubleshooting and resolving MLOps-related issues.


    • Good to have experience with contributing to GitHub and open source initiatives or in research projects
    • Ability to quickly, efficiently, and effectively define and prototype solutions with continual iteration within aggressive product deadlines.
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