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AI Ops / ML Ops Engineer

Dautom
, KSA
Senior
Machine LearningMLOpsDevOpsCI/CDDockerKubernetes
Free

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Job Summary

  • We are looking for an experienced AI Ops / ML Ops Engineer to deploy, monitor, maintain, and optimize AI/ML solutions in production environments.
  • The ideal candidate will have strong expertise in MLOps, DevOps, cloud platforms, Databricks, and AI/ML model lifecycle management.

Key Responsibilities

  • Deploy and manage machine learning models in production.
  • Implement MLOps best practices, CI/CD pipelines, and automation frameworks.
  • Monitor model performance, data drift, system health, and operational metrics.
  • Troubleshoot and support AI/ML applications and services.
  • Maintain model governance, version control, and audit readiness.
  • Improve reliability, scalability, and operational efficiency of AI platforms.
  • Collaborate with Data Science, IT, Architecture, Security, and Business teams.

Required Skills

  • Machine Learning: Supervised & Unsupervised Learning, Deep Learning, Feature Engineering, Model Training & Evaluation, Time Series Forecasting, Model Explainability (SHAP, LIME).
  • MLOps & DevOps: MLflow, Model Registry & Versioning, CI/CD for Machine Learning, Automated Retraining, Model Monitoring & Drift Detection, Kubernetes, Docker, Jenkins / GitHub Actions / Azure DevOps, Infrastructure as Code (Terraform).
  • Databricks: Databricks Lakehouse, Delta Lake, Unity Catalog, Feature Store, Model Serving, Workflows, Delta Live Tables (DLT), Structured Streaming, MLflow Integration.
  • Generative AI / LLMOps: Prompt Engineering, RAG Architecture, Agentic AI, Fine Tuning, LangChain / LangGraph / LlamaIndex, Vector Databases (Pinecone, Weaviate, Chroma, Databricks Vector Search), Foundation Models & LLM Evaluation.
  • AI Operations: Model Performance Monitoring, Data & Concept Drift Detection, Prompt Monitoring, Cost Monitoring, AI Governance, Security & Compliance, Observability & Root Cause Analysis, Prometheus, Grafana, Datadog, Azure Monitor.
  • Cloud (Azure Preferred): Azure Machine Learning, Azure OpenAI Service, Azure AI Search, Azure Data Factory, Azure Databricks, Azure Kubernetes Service (AKS).

Qualifications

  • Bachelor's Degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related field.
  • 7+ years of experience in MLOps, DevOps, AI/ML deployment, cloud platforms, and production support.
  • Relevant certifications in Azure, Databricks, Kubernetes, DevOps, or MLOps are preferred.
  • Arabic and English language skills are an advantage.

Preferred Experience

  • Production AI/ML platforms
  • Databricks ecosystem
  • Azure cloud environment
  • Generative AI and LLMOps implementations
  • Enterprise scale AI governance and monitoring

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