MLOps DeveloperID:59835

3,500 MYR ~ 7,000 MYR马六甲 Malacca约13小时 ago

概述

  • 薪资

    3,500 MYR ~ 7,000 MYR

  • 工作行业

    Manufacturing(Electronics/Semiconductors), Manufacturing(Machinery), Manufacturing(Chemicals/Materials)

  • 工作内容

    We are seeking an MLOps specialist to architect the infrastructure that allows our AI models to live and breathe on the factory floor. You will be the bridge between model development and industrial production, ensuring our AI systems are scalable, monitored, and resilient enough for 24/7 manufacturing operations

    • Model Deployment: Lead the transition of models from Jupyter notebooks into production-ready microservices.
    • Infrastructure Automation: Build and manage the infrastructure required to support LLMs and RAG pipelines at scale.
    • Observability: Implement logging and alerting systems to detect "model drift" or accuracy drops caused by changes in factory sensor data.
    • Security Compliance: Ensure all AI tools and internal chatbots meet enterprise security standards and are integrated with company-wide authentication.
    • Scalability: Optimize AI services to handle high-frequency data from multiple production lines simultaneously.

资格

  • 任职资格

    <Requirements>
    • Min. Bachelor’s Degree in Computer Science, Software Engineering, or a related field.
    • Min. 2-5+ years of professional experience in DevOps or MLOps, with a specific focus on deploying and maintaining machine learning models in production.
    • Strong problem-solving skills and attention to detail
    • Ability to work independently and in a team environment

    <Advantageous>
    • Strong problem-solving and troubleshooting skills.
    • Strong communication and interpersonal skills, with the ability to work effectively in a team.
    • Willingness to work on the shop floor and provide hands-on support.

    <Technical Skills>
    • Automation & CI/CD: Deep expertise in building automated CI/CD pipelines specifically for ML (using Git, Jenkins, or GitHub Actions) and containerization with Docker.
    • Frameworks: Proficiency with ML lifecycle tools like MLflow, Kubeflow, or DVC for model versioning and tracking.
    • Backend: Strong Python skills, particularly for creating robust API endpoints and managing microservices.
    • Security & Monitoring: Experience implementing SSO/MFA for AI services and setting up real-time monitoring for model performance/drift.

  • 英文

    -

  • 其他语言

    Malay, English

附加信息

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