# AI Engineer

> Master-Works · Riyadh, Saudi Arabia · Full-time · Posted 2026-04-07

**Workplace:** on_site

**Department:** Consultation Management

## Description

This is a highly skilled Machine Learning Engineer to design, build, deploy, and scale machine learning models that power data-driven products and intelligent systems. This role sits at the intersection of data science, software engineering, and MLOps, and requires strong hands-on experience turning models into production-ready solutions, programming experience in Python or R.

-   Design, develop, train, and optimize machine learning models for real applications or use cases.
-   Translate business and product requirements into scalable ML/AI solutions.
-   Implement feature engineering, model selection, tuning, and evaluation techniques.
-   Develop , and deploy ML models into production environments with high availability and performance.
-   Build and maintain ML pipelines (training, validation, deployment, monitoring).
-   Monitor model performance, data drift, and model decay; retrain models as needed.
-   Ensure models meet reliability, scalability, and security standards.
-   Work closely with Data Scientists, Product Managers, and Software Engineers.
-   Collaborate with data engineering teams to ensure high-quality, reliable data pipelines.
-   Participate in design and code reviews, ensuring engineering best practices.
-   Optimize models for latency, throughput, and cost.
-   Implement experimentation frameworks (A/B testing, offline evaluation).
-   Apply responsible AI principles, including fairness, explainability, and governance where required.

## Requirements

-   3–7+ years of hands-on experience in Machine Learning or applied AI roles.
-   Strong programming skills in Python (and/or Java, Scala).
-   Solid understanding of ML algorithms (supervised, unsupervised, deep learning).
-   Experience with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
-   Experience deploying models using Docker, Kubernetes, or cloud ML services.
-   Strong knowledge of data structures, algorithms, and software engineering principles.
-   Experience working in agile, cross-functional teams.
-   Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services.
-   Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).
-   Experience with big data technologies (Spark, Kafka, Databricks).
-   Background in NLP, Computer Vision, or Generative AI.
-   Strong problem-solving and analytical thinking
-   Production-first mindset
-   Data-driven decision making
-   High Collaboration and communication skills

## Apply

[Apply at Master-Works](https://apply.workable.com/masterworksco/j/9C06219D13/apply)

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