Machine Learning Engineer 1 - UAE National

noon; Dubai; On-site; AED 320,000 - 650,000; Full time

Job summary

noon in Dubai is seeking an experienced Machine Learning Engineer (MLE1) for Ads to design, train, and deploy production-grade models powering ranking, bidding, and click-fraud detection. You’ll work with product and engineering to translate complex data into competitive advantages.

The role is deeply technical and requires hands-on ML work, strong Python skills, and familiarity with PyTorch, TensorFlow, Scikit-Learn, SQL, and cloud platforms such as GCP.

Qualifications

• Hands-on ML experience or internships preferred.
• Strong grounding in ML concepts, statistics and data structures.
• Proficiency in Python and ML libraries; SQL knowledge.

Responsibilities

• Build, train, and deploy production-grade ML models for Ads.
• Address relevance, ranking, bidding optimization, and fraud detection.
• Collaborate with product and engineering to deploy ML solutions.
• Contribute to standard ML Ops practices within the team.

Skills

Python

ML libraries

SQL

Team collaboration

ML Ops basics

Tools

GCP

Job description

We’re building an ecosystem of digital products and services that power everyday life across the Middle East—fast, scalable, and deeply customer-centric. Our mission is to deliver to every door every day. We want to redefine what technology can do in this region, and we’re looking for a (add title) who can help us move even faster.

noon’s mission: Every door, every day.

What you’ll do:

Team noon has some of the fastest, smartest, and hardest-working people we’ve encountered. As a Machine Learning Engineer (MLE1), Ads, you will be a core individual contributor responsible for the hands-on design, development, and deployment of production-grade Machine Learning models across our Ads division. You will be responsible for delivering high-impact models and deployments that power critical functions like ranking, bidding, and click-fraud detection.

This role is deeply technical; you will partner with Product and Engineering teams across noon Ads to turn complex data into competitive advantages

• Deeply engage in the technical work: building, training, and deploying production-grade models across our domains
• Contribute to solving "hard" problems involving relevance, ranking, bidding optimization, and fraud detection
• Partner with the broader engineering team to implement optimal deployment strategies for heavy ML workloads
• Adhere to and contribute to the standardization of ML Ops and best practices within the team

What you’ll need:

• Experience: hands-on experience or relevant internships in Machine Learning or data science is preferred
• Foundational Knowledge: Strong academic or practical grounding in core machine learning concepts, statistics, and data structures
• Coding & Frameworks: Proficiency in Python and familiarity with standard ML libraries (e.g., PyTorch, TensorFlow, Scikit-learn) and SQL
• Growth & Collaboration: Eagerness to learn from senior engineers, collaborate across product and engineering teams, and rapidly ramp up on MLOps best practices
• Tech Stack: Basic exposure to cloud platforms (like GCP) and data processing pipelines.