Engineer ML

TalentReview AI; Dubai; On-site; AED 112,000 - 134,000; Full time

Job summary

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.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Python

PyTorch

TensorFlow

NumPy

Pandas

Scikit-learn

Docker

Kubernetes

CI/CD

SQL

NoSQL

AWS

Azure

GCP

MLflow

Kubeflow

ClearML

Education

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

Tools

Docker

Kubernetes

CI/CD tools

PostgreSQL/MySQL

MongoDB

Elasticsearch

Job description

Job Description:

Job Description: Machine Learning Engineer (MLOps)

Job Title: Machine Learning Engineer (MLOps)

Location: Dubai, UAE

Work Arrangement: On-site - Candidates must currently be based in Dubai

Duration: 12 Months Monthly Rate: AED 11,000

Experience: 5-9 Years

Employment Type: Contract

Position Summary

We are seeking an experienced Machine Learning Engineer (MLOps) to develop, deploy, monitor, and optimise machine-learning models and AI pipelines for production environments. The ideal candidate will have strong expertise in Python, machine-learning frameworks, MLOps practices, cloud platforms, and containerisation technologies.

The candidate will be responsible for transitioning machine-learning models from proof of concept (PoC) to scalable production deployment across cloud and edge environments, ensuring performance, reliability, and resource efficiency.

Important: Only candidates currently residing in Dubai, UAE, will be considered.

Key Responsibilities

• Model Deployment: Deploy machine-learning models and AI pipelines from development and PoC stages into production using CI/CD pipelines, containerisation, and orchestration tools.
• Monitoring and Maintenance: Implement model monitoring, performance tracking, drift detection, and maintenance strategies to ensure accuracy and reliability.
• Model Optimisation: Optimise models for inference speed and resource efficiency using quantisation, pruning, and knowledge distillation techniques.
• Data Preprocessing: Perform data collection, cleaning, transformation, and feature engineering to prepare datasets for training and evaluation.
• Model Training and Tuning: Develop continuous or semi-continuous training and evaluation workflows, fine-tune models, and maintain model performance over time.
• MLOps Implementation: Build and maintain automated ML pipelines, model versioning, experiment tracking, and deployment workflows.
• Cloud and Edge Deployment: Deploy and optimise ML solutions across cloud platforms and edge devices, including resource-constrained environments.
• Cross-Functional Collaboration: Work closely with data scientists, software engineers, DevOps teams, and product managers to translate business requirements into effective ML solutions.
• Documentation: Maintain comprehensive documentation of source code, models, deployment processes, pipelines, and operational procedures.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, Artificial Intelligence, or a related field.
• 5-9 years of relevant experience in machine learning engineering, AI engineering, or MLOps.
• Strong programming skills in Python.
• Hands-on experience with PyTorch, TensorFlow, NumPy, Pandas, and Scikit-learn.
• Experience deploying machine-learning models in production environments.
• Knowledge of Docker, Kubernetes, and CI/CD pipeline implementation.
• Experience working with SQL and NoSQL databases.
• Familiarity with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Experience with MLOps tools such as MLflow, ClearML, Azure Machine Learning, AWS SageMaker, or Kubeflow.
• Strong understanding of deep learning, reinforcement learning, model evaluation, and optimisation techniques.
• Understanding of model monitoring, performance tuning, and production troubleshooting.

Preferred Qualifications

• Experience deploying computer-vision models to edge devices or low-resource environments.
• Familiarity with infrastructure-as-code tools and observability platforms.
• Experience with GPU-based computing and model acceleration.
• Contributions to open-source computer-vision projects or relevant research publications.
• Experience with distributed computing frameworks and large-scale ML pipelines.

Core Technical Skills

• Programming Language
• Python
• Frameworks and Libraries
• PyTorch, TensorFlow, OpenCV, Scikit-learn, Pandas, NumPy, FastAPI
• MLOps and Model Management
• MLflow, Kubeflow, ClearML, Ray
• Deployment and CI/CD
• Docker, Kubernetes, GitLab CI/CD
• Databases and Search Technologies
• PostgreSQL, MySQL, MongoDB, Elasticsearch, Neo4j
• Deep Learning Architectures
• CNN, LSTM, GANs, Transformers, Large Language Models (LLMs)
• Distributed Computing, Messaging and GPU Technologies
• RabbitMQ, Kafka, CUDA, RAPIDS, Numba
• Cloud Platforms
• AWS, Microsoft Azure, Google Cloud Platform (GCP)

Candidate Requirements

• Must currently be based in Dubai, UAE.
• Must be available to work on-site in Dubai.
• Must be comfortable with a 12-month contract.
• Must be able to work within the proposed monthly rate of AED 11,000.

Requirements: