MLOps Engineer

4 weeks ago

Bengaluru, India Zyoin group Full time

Responsibilities :

  • Strategize, plan, and deliver MLOps initiatives by liaising with key business stakeholders.
  • Design, develop, and deploy complex AI/ML solutions on cloud infrastructure (using ML engineering, ML Ops workflows & tools) that can scale in response to changing business and technical requirements.
  • Create infra and architecture diagrams.
  • Ability to project manage, allocate activities to junior/senior ML engineers, and take them to closure.
  • Improvise coding practices, support code reviews and bring in best practices for model management.
  • Provide thought leadership in terms of new technologies and tools, and suggest improvements.
  • Able to support the interview process to hire junior and senior ML engineers.


Role :

  • Containerization and Orchestration : Deploy and manage machine learning models in production environments using Docker for containerization and Kubernetes for orchestration, ensuring scalability and reliability.
  • MLOps Implementation: Establish and maintain MLOps pipelines, incorporating version control, continuous integration, and continuous deployment practices to streamline the machine learning model deployment lifecycle.
  • Monitoring and Optimization: Implement monitoring solutions for deployed machine learning models, and continuously optimize infrastructure and workflows for performance and resource efficiency.
  • Collaboration: Collaborate with data scientists, machine learning engineers, and DevOps teams to bridge the gap between development and operations, facilitating seamless integration of machine learning into the overall software development lifecycle.
  • Security and Compliance: Implement security best practices in MLOps workflows, ensuring the confidentiality and integrity of machine learning models and data, and adhering to regulatory compliance requirements.
(ref:hirist.tech)

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