Production ML Engineer - Scale Real-World AI

Master-Works; Riyadh; On-site; SAR 240,000 - 420,000; Full time

Job summary

Master Works is seeking a highly skilled Machine Learning Engineer to design, build, deploy, and scale ML models powering data-driven products and intelligent systems. The role intersects Data Science, Software Engineering, and MLOps, with hands-on experience turning models into production-ready solutions.

You will collaborate with DS, PM, SWE, and Data Eng teams to develop scalable AI solutions, optimize model performance, and support enterprise AI initiatives aligned with engineering best

Qualifications

• Bachelor's degree in a relevant field.
• 3–7+ years hands-on ML/AI experience.
• Strong Python and/or Java/Scala programming.
• Solid understanding of ML algorithms (supervised, unsupervised, DL).
• Hands-on experience with TF, PyTorch, Scikit-learn.
• Experience deploying ML models with Docker/Kubernetes or cloud ML services.
• Strong software engineering fundamentals (data structures & algorithms).
• Experience in Agile, cross-functional delivery teams.
• Experience with cloud platforms (AWS/Azure/GCP).
• Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).
• Familiarity with big data: Spark, Kafka, Databricks.
• Background in NLP, CV, or Generative AI is preferred.
• Strong analytical, problem-solving, collaboration, and communication skills.
• Experience building enterprise-scale AI/ML platforms.
• Familiarity with Responsible AI and AI governance practices.
• Experience supporting production-grade AI systems and high-scale ML deployments.

Responsibilities

• Design, develop, train, optimize, and deploy ML models for real-world business use cases.
• Translate requirements into scalable ML and AI solutions.
• Implement feature engineering, model selection, tuning, validation, and evaluation.
• Deploy ML models into production with high availability and performance.
• Build and maintain ML pipelines for training, validation, deployment, and monitoring.
• Monitor performance, data drift, and model decay; support retraining.
• Ensure ML solutions meet reliability, scalability, governance, and security standards.
• Collaborate with cross-functional teams including DS, PM, SWE, and Data Eng.
• Support development and maintenance of high-quality data pipelines.
• Participate in architecture reviews, design reviews, and code reviews.
• Optimize models for latency, throughput, scalability, and cost efficiency.
• Implement experimentation and evaluation frameworks (A/B tests, offline evals).
• Apply Responsible AI principles including fairness, explainability, governance.

Skills

Python

Java/Scala

Machine Learning

Supervised/Unsupervised/DL

Agile / cross-functional

Data Structures & Algorithms

Cloud platforms (AWS/Azure/GCP)

MLOps (MLflow/Kubeflow/Airflow)

Docker/Kubernetes

NLP/CV/Generative AI (pref)

Big data tools (Spark, Kafka, Databr"b

Education

Bachelor’s degree in Computer Science, AI, Data Science, Software Engineering, or related field

Tools

TensorFlow

PyTorch

Scikit-learn

Docker

Kubernetes

SageMaker/Azure ML/GCP ML services

Job description

Master Works is seeking a highly skilled Machine Learning Engineer to design, build, deploy, and scale ML models powering data-driven products and intelligent systems. The role intersects Data Science, Software Engineering, and MLOps, with hands-on experience turning models into production-ready solutions.

You will collaborate with DS, PM, SWE, and Data Eng teams to develop scalable AI solutions, optimize model performance, and support enterprise AI initiatives aligned with engineering best