Staff Machine Learning Engineer

noon; Dubai; On-site; AED 200,000 - 300,000; Full time

Job summary

A leading technology firm in Dubai is seeking a Staff Machine Learning Engineer to architect and deliver machine learning intelligence for their next generation products. The role involves designing and deploying ML models that impact a vast e-commerce footprint, collaborating with cross-functional teams, and providing technical leadership. Candidates should have over 6 years of applied ML experience and strong skills in Python and ML frameworks, with knowledge in cloud platforms being a bonus.

Qualifications

• 6+ years of experience in applied ML engineering.
• Bachelor's degree in a relevant field; master's or PhD is a plus.
• Strong proficiency with Python and modern ML frameworks.
• Proven experience in deploying ML models with CI/CD.
• Strong SQL and data engineering fundamentals.

Responsibilities

• Design, train, and deploy ML models for e-commerce.
• Architect reliable ML training and deployment pipelines.
• Hire and mentor ML engineers across Labs.
• Collaborate with product and engineering leaders.

Skills

Applied machine learning engineering

Python

ML frameworks (PyTorch, TensorFlow, etc.)

SQL

Data engineering fundamentals

CI/CD

Cloud platforms (AWS, GCP, Azure)

Generative AI or NLP systems

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Airflow

TensorFlow

Scikit-learn

XGBoost

Airflow

Job description

Staff Machine Learning Engineer Jobs in Dubai, UAE

About the role

As a Staff Machine Learning Engineer at Everyday Labs, you will architect and deliver the intelligence that powers our next generation of products, experiments, and ventures. You will work at the intersection of applied machine learning, experimentation, and scalable engineering — building models and ML infrastructure that can go from idea to deployed value with exceptional velocity and rigor. This is a highly technical, high-ownership role where you will influence technical strategy, hire and mentor engineers, and help shape the culture and systems that allow ML ideas to become high-impact reality.

Machine Learning: Turning Ideas into Value

• Design, train, and deploy ML models that deliver measurable impact across multiple aspects of noon’s vast e-commerce footprint.
• Translate ambiguous or zero-to-one problems into clear hypotheses, measurable signals, and verifiable ML solutions.
• Collaboration with product, engineering and business leaders to define value metrics and success thresholds early and rigorously.

Production ML Systems & Pipelines

• Architect reliable training, validation, and deployment pipelines using modern MLOps practices.
• Build and maintain feature stores, automated retraining systems, online inference services, and monitoring frameworks.
• Ensure systems meet high bars for observability, reliability, and performance — excellence in execution is part of our signature.

Technical Leadership & Cross-Team Ownership

• Hire and mentor ML and software engineers across Labs in traditional ML, generative AI technologies.
• Contribute to cross-initiative architecture, documentation, and open knowledge sharing.
• Work noon partners and stakeholders to apply ML where it can unlock disproportionate impact.

What you’ll need:

• 6+ years of experience in applied ML engineering
• Bachelor’s degree in Computer Science, Engineering, or a related technical field, master’s or PhD is a plus but not required.
• Strong proficiency with Python, modern ML frameworks (PyTorch, TensorFlow, Scikit-learn, XGBoost), and model lifecycle best practices.
• Proven experience deploying ML models into real-world systems with CI/CD and automated monitoring.
• Strong SQL and data engineering fundamentals, including building scalable data pipelines (Airflow or similar).
• Experience with cloud platforms (AWS, GCP, Azure). GCP is a plus.
• Experience with generative AI, LLMs, or NLP systems is a strong bonus.