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    Senior MLOps Engineer - Plano, United States - Ascentt

    Ascentt
    Ascentt Plano, United States

    1 month ago

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    Description

    Job Title: MLOps Engineer

    Location: Dallas, TX

    Job Type: Full-time

    Responsibilities:

    • MLOps and DevOps Integration:
      • Design, implement, and manage end-to-end Machine Learning Operations (MLOps) processes.
      • Collaborate with cross-functional teams to integrate ML models seamlessly into production using tools.
    • Machine Learning Lifecycle Management:
      • Drive the implementation of best practices for ML model deployment, monitoring, and maintenance throughout the entire ML lifecycle.
      • Work closely with Data Scientists and DevOps teams to streamline the deployment process and ensure scalability.
    • Infrastructure and Containerization:
      • Utilize Docker for containerization to ensure consistent and reproducible deployment environments.
      • Implement and maintain infrastructure as code using tools like Terraform.
    • GitHub Actions and CI/CD:
      • Design and maintain robust CI/CD pipelines using GitHub Actions to automate the ML model deployment process.
      • Ensure efficient version control and collaboration among team members.
    • Amazon SageMaker Expertise:
      • Possess a deep understanding of Amazon SageMaker for scalable and cost-effective ML model training and deployment on AWS.
      • Optimize and fine-tune SageMaker processes for enhanced performance.
    • Weights and Biases Integration:
      • Leverage expertise in the Weights and Biases tool to improve model training, experimentation, and monitoring.
      • Implement and maintain W&B integrations to enhance visibility and collaboration across the ML team.

      Qualifications:

      • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
      • Proven experience in MLOps, DevOps, and Machine Learning lifecycle management.
      • Strong proficiency with Docker and container orchestration tools.
      • In-depth knowledge of GitHub Actions for CI/CD workflows.
      • Hands-on experience with Amazon SageMaker and AWS services.
      • Familiarity with infrastructure as code (e.g., Terraform).
      • Previous work with Weights and Biases tool.
      • Excellent problem-solving skills and attention to detail.
      • Strong communication and collaboration skills.

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