Dubai ML Engineer (MLOps): Production Pipelines

Connect Tech+Talent; Dubai; On-site; AED 150,000 - 230,000; Full time

Job summary

Connect Tech+Talent is seeking an ML Engineer (MLOps) in Dubai to take machine-learning models from PoC to production across edge and cloud environments. You will own deployment, monitoring, and optimization, collaborating with data scientists, software engineers, DevOps, and product managers.

The role requires deep learning expertise, hands-on experience with PyTorch, Docker, Kubernetes, and cloud platforms, and a strong track record deploying scalable ML pipelines in production.

Qualifications

• Bachelor's or master's in CS/ML/DS/AI or related field.
• 5–9 years of relevant experience.
• Proficiency in Python and libraries (PyTorch, NumPy, Pandas, Scikit-learn).
• Experience with Docker and Kubernetes for deployment.
• Strong SQL and NoSQL database knowledge.
• Cloud experience (AWS, GCP, or Azure).
• Familiarity with MLflow, ClearML, Azure ML or SageMaker.
• Strong understanding of deep learning and reinforcement learning.

Responsibilities

• Deployment: Deploy ML models and AI pipelines from PoC to production with scalable CI/CD.
• Monitoring & Maintenance: Implement monitoring for ongoing accuracy and reliability.
• Model Optimisation & Pruning: Optimise for edge and cloud deployment.
• Data Preprocessing: Collect, clean and engineer features for training.
• Model Training & Tuning: Implement continuous training and evaluation workflows.
• Collaboration: Work with data scientists, software engineers, DevOps, and PMs.
• Documentation: Maintain clear documentation of code, models, and processes.

Skills

Python

PyTorch

NumPy

Pandas

Scikit-learn

Deep learning

Reinforcement learning

ML deployment

Education

Bachelor's or Master's degree in Computer Science, ML, DS, AI or related field

Tools

Docker

Kubernetes

SQL

NoSQL

AWS

GCP

Azure

MLflow

ClearML

Azure ML

SageMaker

TensorFlow

OpenCV

Job description

Connect Tech+Talent is seeking an ML Engineer (MLOps) in Dubai to take machine-learning models from PoC to production across edge and cloud environments. You will own deployment, monitoring, and optimization, collaborating with data scientists, software engineers, DevOps, and product managers.

The role requires deep learning expertise, hands-on experience with PyTorch, Docker, Kubernetes, and cloud platforms, and a strong track record deploying scalable ML pipelines in production.