Job Title: MLOps & AI Platform Engineer
Experience: 3–11 Years
Location: Riyadh - Onsite
Employment Type: Full-Time
We are seeking a skilled MLOps & AI Platform Engineer with 3–11 years of experience to build, automate, and manage scalable machine learning platforms and production AI environments. The ideal candidate will have hands-on expertise in MLOps, Kubernetes, cloud-native AI infrastructure, CI/CD automation, and model lifecycle management. You will be responsible for enabling data scientists and AI engineers to efficiently develop, deploy, monitor, and maintain machine learning models at scale.
Key Responsibilities- Design, build, and maintain enterprise-grade MLOps platforms and AI infrastructure.
- Develop and automate end-to-end machine learning pipelines for training, validation, deployment, and monitoring.
- Implement model versioning, experiment tracking, and model registry solutions.
- Build scalable CI/CD pipelines for AI/ML workloads.
- Deploy and manage machine learning workloads on Kubernetes-based environments.
- Collaborate with Data Scientists, AI Engineers, Data Engineers, and DevOps teams to operationalize ML solutions.
- Implement Infrastructure as Code (IaC) for cloud-native AI platforms.
- Monitor platform health, model performance, and infrastructure availability.
- Ensure platform security, scalability, reliability, and operational excellence.
- Troubleshoot production issues and continuously optimize platform performance.
- Hands-on experience with Kubeflow or Vertex AI Pipelines or SageMaker Pipelines.
- Strong experience with MLflow for experiment tracking, model registry, and lifecycle management.
- Experience orchestrating machine learning workflows using Apache Airflow.
- Strong expertise in Kubernetes (GKE or AKS or EKS).
- Experience deploying and managing containerized AI/ML workloads in cloud environments.
- Hands-on experience with Terraform for Infrastructure as Code (IaC).
- Experience automating infrastructure provisioning and cloud resource management.
- Experience with GitHub Actions for CI/CD automation.
- Knowledge of DevOps best practices, Git workflows, and automated deployments.
- Experience using Prometheus for infrastructure and application monitoring.
- Knowledge of logging, alerting, and performance monitoring for AI platforms.
- Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Information Technology, or a related field.
- 3–11 years of professional experience in MLOps, DevOps, Platform Engineering, Cloud Engineering, or AI Infrastructure.
- Strong scripting and automation skills using Python, Bash, or similar languages.
- Excellent analytical and problem-solving skills.
- Experience working in Agile/Scrum environments.
- Experience with Docker and containerized application deployment.
- Knowledge of cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
- Familiarity with model monitoring, drift detection, and automated retraining pipelines.
- Experience implementing security best practices for AI/ML platforms.
- Cloud and Kubernetes certifications are a plus.
- MLOps Platforms: Kubeflow or Vertex AI Pipelines or SageMaker Pipelines
- Workflow Orchestration: Apache Airflow and MLflow
- Container Orchestration: Kubernetes (GKE or AKS or EKS)
- Infrastructure as Code: Terraform
- CI/CD: GitHub Actions
- Monitoring: Prometheus
- Cloud Platforms: Google Cloud Platform or Microsoft Azure or Amazon Web Services (Preferred)
- Automation: Python and Bash (Preferred)
Skills Required
- Bachelor's degree in Computer Science, Software Engineering, AI, IT, or related field
- 3-11 years professional experience in MLOps, DevOps, Platform Engineering, Cloud Engineering, or AI Infrastructure
- Hands-on experience with Kubeflow or Vertex AI Pipelines or SageMaker Pipelines
- Strong experience with MLflow for experiment tracking and model registry
- Experience orchestrating ML workflows using Apache Airflow
- Strong expertise in Kubernetes (GKE or AKS or EKS) and deploying ML workloads on Kubernetes
- Hands-on experience with Terraform for Infrastructure as Code
- Experience building CI/CD pipelines using GitHub Actions and Git workflows
- Experience with Prometheus for monitoring and observability
- Strong scripting and automation skills using Python
- Scripting/automation skills using Bash
- Experience working in Agile/Scrum environments
- Experience with Docker and containerized application deployment
- Knowledge of cloud platforms such as AWS, Azure, or GCP
- Familiarity with model monitoring, drift detection, and automated retraining pipelines
- Experience implementing security best practices for AI/ML platforms
- Cloud and Kubernetes certifications
Datamatics Technologies Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Datamatics Technologies and has not been reviewed or approved by Datamatics Technologies.
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Flexible Benefits — Feedback suggests flexible timings and work-from-home options are available in some roles. This flexibility is highlighted as part of the employment experience across certain postings and materials.
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Wellbeing & Lifestyle Benefits — Feedback suggests flexibility around time off and remote work supports work-life balance. These elements can help offset leaner cash components for some individuals.
Datamatics Technologies Insights
What We Do
Datamatics Technologies (DMT) was established in Dubai. We specialize in providing onsite and offshore professional services, covering the full spectrum of Data Analytics and Data Science domains. Our experience of working with diverse industry sectors such as Telecoms, Finance, Government and Manufacturing, across multiple regions enables us to engage and deliver for our clients with confidence. We can offer our full portfolio of services through resource augmentation, managed services, both on T&M or fixed price financial arrangements. Through our end-to-end managed services offering we enable our clients to cut down costs, increase profitability and focus on value addition to their core business activities. Our project and delivery management team are certified in Agile, PMI and ITIL to ensure the planning and execution are carried out using industry best practices. We are working with our clients across Middle East and Africa Region.
