AI/ML Ops Engineer

Michael Page; Dubai; On-site; AED 120,000 - 200,000; Full time

Job summary

A leading recruitment agency is seeking an MLOps Engineer to design, deploy, and maintain AI/ML solutions in Dubai. In this role, you'll collaborate with various teams to ensure models are production-ready, focusing on pricing models and logistics. Ideal candidates should have over 4 years of experience in MLOps, strong Python skills, and familiarity with ML frameworks. Competitive opportunity to work at the forefront of AI innovation in logistics.

Benefits

Opportunity to work on innovative AI solutions

Collaboration with top-tier teams

Qualifications

• 4+ years of hands-on experience in MLOps.
• Experience deploying and managing ML models in production.
• Strong background in pricing optimisation and logistics AI solutions.

Responsibilities

• Build and maintain scalable ML pipelines for pricing optimisation.
• Deploy and manage ML models in production using MLOps frameworks.
• Collaborate with data scientists to take prototypes to production.

Skills

MLOps

AI/ML

Python

TensorFlow

Scikit-learn

Docker

Kubernetes

Education

Bachelor's/Master's in Computer Science, Data Science or related field

Tools

MLflow

Kubeflow

SageMaker

Vertex AI

Azure ML

Job description

Overview

You will be at the core of designing, deploying, and maintaining robust AI/ML solutions in production, with a strong focus on pricing models, demand forecasting, route optimisation, and real-time logistics decision-making. Working closely with Data Science, Engineering, and Product teams, you'll ensure models are production-ready, scalable, and delivering measurable impact.

Responsibilities

• Build and maintain scalable ML pipelines for pricing optimisation, shipping rate prediction, and logistics operations.
• Deploy, monitor, and manage ML models in production using best-practice MLOps frameworks and tools.
• Collaborate with data scientists to take prototypes through to production-grade solutions.
• Implement automated model monitoring, retraining, and version control processes to ensure performance stability.
• Optimise model latency and cost efficiency for real-time decision-making in high-volume transactional environments.
• Partner with engineering teams to streamline data flows from operational systems (ERP, WMS, TMS) and ensure data readiness.
• Champion reproducibility, scalability, and operational excellence in AI delivery.

Profile

• Bachelor's/Master's in Computer Science, Data Science, Engineering, or related field.
• 4+ years of hands-on experience in MLOps, with a strong background in deploying and managing ML models in production.
• Proven experience in pricing optimisation, shipping, logistics, or supply chain AI solutions.
• Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Familiarity with MLOps tools and platforms (MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML).
• Solid understanding of CI/CD, containerisation (Docker, Kubernetes), and cloud-based ML infrastructure.
• Experience working with APIs and integrating ML into operational workflows.

Job Offer

Opportunity to work at the intersection of AI innovation and real-world logistics challenges.

Skills

• AI/ML Ops