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Machine Learning Engineer
Purpose:
- Designs, develops, and deploys machine learning models and pipelines to support data-driven applications and services across the AI portfolio
Responsibilities:
- Design and develop machine learning models to solve business problems; Build and maintain scalable ML pipelines from data preprocessing to deployment.
- Collaborate with data scientists and engineers to integrate models into production systems
- Monitor and optimize model performance in real-time environments; Implement versioning, reproducibility, and tracking of ML experiments
- Contribute to code reviews and ML framework standardization
Requirements:
- Degree in Computing, Engineering, Computer Science, Machine Learning or AI with 3 - 5 years of experience in ML model development and deployment.
- Proficiency in Python, TensorFlow, PyTorch, or Scikit-learn; Experience with MLOps tools (MLflow, Kubeflow, SageMaker, etc.)
- Strong knowledge of data structures, software engineering, and cloud ML infrastructure
- Understanding of CI/CD pipelines and containerized deployments (e.g., Docker, Kubernetes)
- Strong problem-solving and debugging skills; Collaboration with cross-functional teams
- Clear documentation and communication of model behavior
Key Skills
Ranked by relevance
machine learning
ai
data structures
tensorflow
kubeflow
pytorch
python
docker
mlflow
cloud
mlops
cicd
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- Posted
- Nov 06, 2025
- Type
- Full-time
- Level
- Mid-Senior
- Location
- Dubai
- Company
- nSearch Global
Industries
Information Technology & Services
IT Services
IT Consulting
Data Infrastructure
Analytics
Categories
Information Technology
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