Dubai-based MLOps Engineer – On-Site (12-Month Contract)

TalentReview AI; Dubai; Vor Ort; AED 112.000 - 134.000; Vollzeit

Zusammenfassung

TalentReview AI in Dubai seeks an experienced Machine Learning Engineer (MLOps) to develop, deploy, monitor, and optimise ML models and AI pipelines for production environments.

The ideal candidate has strong Python, ML frameworks, cloud platforms, and containerisation experience, with a focus on transitioning PoCs to scalable deployments across cloud and edge environments. On-site in Dubai is required.

Qualifikationen

• Bachelor's or Master's degree in Computer Science, ML/AI or related field.
• 5-9 years of ML engineering, AI engineering, or MLOps experience.
• Strong Python programming skills.
• Hands-on with PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn.
• Experience deploying ML models in production with CI/CD, Docker & Kubernetes.
• Cloud familiarity: AWS/Azure/GCP; MLflow/Kubeflow/ClearML experience.

Aufgaben

• Deploy ML models and AI pipelines from PoC to production using CI/CD and containerization.
• Implement model monitoring, drift detection, and maintenance strategies.
• Optimize models for inference speed and efficiency (quantisation, pruning, distillation).
• Prepare data: collection, cleaning, transformation, feature engineering.
• Develop continuous or semi-continuous training/workflows and tune models.
• Build and maintain automated ML pipelines, versioning, experiment tracking.

Kenntnisse

Python

PyTorch

TensorFlow

NumPy

Pandas

Scikit-learn

Docker

Kubernetes

CI/CD

SQL

NoSQL

AWS

Azure

GCP

MLflow

Kubeflow

ClearML

Ausbildung

Bachelor's or Master's in CS/ML/AI

Tools

Docker

Kubernetes

CI/CD tools

PostgreSQL/MySQL

MongoDB

Elasticsearch

Jobbeschreibung

TalentReview AI in Dubai seeks an experienced Machine Learning Engineer (MLOps) to develop, deploy, monitor, and optimise ML models and AI pipelines for production environments.

The ideal candidate has strong Python, ML frameworks, cloud platforms, and containerisation experience, with a focus on transitioning PoCs to scalable deployments across cloud and edge environments. On-site in Dubai is required.