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PurpleElife

MLOps

RemotePart-timeAED 20,000 - AED 35,000Posted Mar 9, 2026
MLOpsKubernetesDockerCI/CDTensorFlowAWSML pipelinesModel monitoring

Role overview

Join our dynamic team as an MLOps Specialist and play a pivotal role in driving the deployment, automation, and scalability of cutting-edge machine learning models. This part-time, remote position offers you the opportunity to impact innovation in real-time, working alongside top-tier professionals to streamline ML workflows and enhance operational efficiency. If you thrive in fast-paced environments and are passionate about bridging the gap between data science and IT, this role is your gateway to making a tangible difference in the future of AI-driven solutions. What We Offer: - Competitive salary range of AED 20,000 - AED 35,000 tailored to your expertise. - Flexible remote work environment empowering work-life balance. - Access to advanced tools and platforms to elevate your MLOps skills. - Collaborative culture that values innovation, continuous learning, and professional growth.

What you will do

  • Design, implement, and maintain scalable MLOps pipelines for model deployment and monitoring.
  • Collaborate with data scientists and engineers to automate model training, testing, and deployment workflows.
  • Ensure reliability and performance of ML models in production environments through continuous integration and continuous delivery (CI/CD) practices.
  • Monitor model performance and implement strategies for model retraining and versioning.
  • Optimize infrastructure for cost-effective and efficient ML operations.
  • Develop and maintain documentation for MLOps processes and best practices.
  • Troubleshoot and resolve issues related to model deployment and operational workflows.

Skills profile

Required skills

MLOpsKubernetesDockerCI/CDTensorFlowAWSML pipelinesModel monitoring

Required qualifications

Additional requirements

  • Proven experience in MLOps, DevOps, or related roles with a focus on machine learning models.
  • Strong proficiency with cloud platforms such as AWS, Azure, or Google Cloud.
  • Hands-on experience with containerization (Docker, Kubernetes) and CI/CD tools.
  • Familiarity with ML frameworks (TensorFlow, PyTorch, etc.) and model serving technologies.
  • Solid understanding of software development lifecycle and automation tools.
  • Excellent problem-solving skills and ability to work independently in a remote setup.