Jobs

    Machine Learning Engineer - Pune, India - Technomech Placements

    Technomech Placements
    Technomech Placements Pune, India

    2 weeks ago

    Default job background
    permanent Technology / Internet
    Description


    Job Description :

    Position :
    ML Engineer & ML Ops.

    Experience : 6 years.

    Location - Pune - Hybrid.

    Job Type - Fulltime.

    Here we are looking for strong ML Ops Exp using Sage maker.


    Skill Set :
    Machine Learning.


    Sub Skill :
    Azure, GCP, AWS, Devops, Python, Kubernetes, Containerization, Machine Learning.



    Job Description :

    End-to-End ML Lifecycle Management :

    • Design and implement endtoend Machine Learning (ML) pipelines, from data preparation to model deployment and monitoring.
    • Collaborate with data scientists and engineers to streamline the ML workflow and ensure scalability.

    Model Deployment and Monitoring :

    • Deploy ML models into production environments and monitor their performance.
    • Implement automated monitoring and alerting systems to detect and respond to model drift or degradation.

    Infrastructure and Environment Management :

    • Work closely with DevOps teams to manage infrastructure for ML workloads, ensuring scalability, reliability, and security.
    • Implement containerization and orchestration solutions for ML applications.

    Collaboration and Documentation :

    • Collaborate with crossfunctional teams, including data scientists, software engineers, and business stakeholders.
    • Document MLOps processes, best practices, and guidelines.

    Requirements:

    Experience :
    Overall Experience of minimum 6 years with 2-3 years of relevant experience in MLOps.


    Technical Skills :

    • Proficient in programming languages such as Python and experience with ML frameworks.
    • Knowledge of containerization (Docker) and orchestration (Kubernetes) technologies.

    Infrastructure and Cloud :

    • Experience with of deploying at least 2 AI/ML Projects on AWS SageMaker.
    • Exposure to Azure DevOps.
    • Familiarity with infrastructure as code (IaC) tools.

    Collaboration and Communication:

    • Strong communication and collaboration skills, with the ability to work effectively in a crossfunctional team.
    • Problemsolving Skills
    Proven ability to troubleshoot complex issues and find practical solutions.

    )
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