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    NStarX - MLOps Engineer - AWS/Python - Hyderabad, India - Nstarx India Private Limited

    Nstarx India Private Limited
    Nstarx India Private Limited Hyderabad, India

    2 days ago

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    Description

    Job Description :

    Key Qualifications :
    Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.

    • Minimum of 3 years of experience in machine learning engineering, with a proven track record of deploying scalable ML solutions on AWS.
    • Strong proficiency in Python, with handson experience in ML libraries (e.g., TensorFlow, PyTorch, Scikit learn).

    Technical Skills and Experience :

    AWS Expertise :

    • Extensive experience with AWS services related to ML and data processing, such as AWS Sagemaker, Lambda, S3, Glue, and EC2.
    • Proficiency in building and managing data processing pipelines utilizing AWS technologies.

    CI/CD Pipeline Development :

    • Solid understanding of CI/CD principles and experience in building and maintaining CI/CD pipelines specifically for ML workflows on AWS.
    • Familiarity with tools like AWS CodePipeline, CodeBuild, and Jenkins or GitLab for automation.

    ML Engineering Architecture Optimization :

    • Experience in optimizing ML architectures on AWS, including effective use of Lambda functions for scalable, eventdriven ML processes.
    • Knowledge of containerization technologies (Docker, Kubernetes) and serverless architectures.

    Model Governance and Deployment :

    • Proven ability to set up model governance frameworks ensuring model quality, reproducibility, and auditability.
    • Experience in developing model deployment pipelines, ensuring models are robustly tested, versioncontrolled, and easily rolled out or rolled back.

    ML Model Development and Testing :

    • Strong background in developing, evaluating, and iterating on ML models to meet project objectives.
    • Proficiency in model testing techniques, including A/B testing and performance monitoring.

    Responsibilities :

    • Design, develop, and maintain scalable data processing and ML pipelines on AWS, ensuring best practices in data handling and processing.
    • Implement and optimize CI/CD pipelines for automated testing, integration, and deployment of ML models.
    • Collaborate with data scientists and engineers to optimize ML engineering architecture on AWS, focusing on efficiency and scalability.
    • Establish robust model governance practices, including model versioning, auditing, and compliance with industry standards.
    • Continuously research and apply the latest ML technologies and methodologies to enhance project outcomes.
    )
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