Machine Learning Engineer

About the role

Arabic.AI is looking for a Machine Learning Engineer in Riyadh to turn machine-learning ideas into production and build the dashboards and reports that decision-makers rely on. The role covers about twenty use cases and twenty dashboards per year, using Python and Dataiku for the models and Qlik, Power BI and Python for the visuals. It combines the data-science and analysis side of the project with business intelligence.

Key responsibilities

• Qualify and prioritise use cases with the client, then build, deploy and monitor the models.
• Carry out the statistical analysis behind each use case and explain the results to non-technical stakeholders.
• Design and build dashboards and automated reports in Arabic and English.
• Train only on masked or de-identified data and document the features and data used.
• Keep models and dashboards healthy through retraining, drift monitoring, scheduled refreshes and performance checks.
• Help write the monthly progress report for the AI and dashboard work.

Required profile

• Experience with the Python ML stack (pandas, scikit-learn and one of PyTorch, TensorFlow or XGBoost), including models run in production.
• Experience with forecasting, segmentation, recommendation and NLP use cases.
• MLOps: reproducible training, deployment, monitoring and retraining.
• Statistical analysis and experiment design.
• Right-to-left, bilingual dashboard design and privacy-aware practices such as masking and de-identification.

Required skills

• Qlik Sense: load scripts, associative model, set analysis, section access, report automation.
• Power BI: data model, DAX, Power Query, row-level security, scheduled refresh.
• Python reporting and visualisation (Plotly or Dash, Streamlit or similar).
• Nice to have: Arabic NLP, Vertex AI or BigQuery ML, marketing-mix, attribution or uplift modelling, Qlik or Power BI certification, Google Professional Machine Learning Engineer.