AI/ML Engineer — Deploy Scalable Models (Remote)

HUMAN-AI-Z Nexus Technology; Dubai; Hybrid; AED 734,000 - 1,836,000; Full time

Job summary

HUMAN-AI-Z Nexus Technology is seeking an AI Engineer to develop and deploy machine learning models powering core product features. This hybrid role involves collaborating with cross-functional teams to design scalable AI solutions that enhance user experience and operational efficiency.

The ideal candidate will have strong Python, TensorFlow, and PyTorch skills, plus experience with MLOps and cloud platforms.

Qualifications

• Proficiency in Python, TensorFlow, and PyTorch for model development and training.
• Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker for deployment and monitoring.
• Strong background in data preprocessing, feature engineering, and model evaluation metrics.
• Familiarity with cloud platforms (AWS, GCP, or Azure) for scalable AI infrastructure.
• Knowledge of software engineering best practices, including version control (Git) and CI/CD pipelines.

Responsibilities

• Design, train, and optimize machine learning models using Python, Tensor Flow, and PyTorch frameworks.
• Develop and maintain data pipelines to ensure high-quality input for model training and evaluation.
• Implement MLOps practices to streamline model deployment, monitoring, and version control.
• Collaborate with data scientists and software engineers to integrate AI capabilities into production systems.
• Conduct performance benchmarking and A/B testing to validate model accuracy and business impact.

Skills

Python

TensorFlow

PyTorch

Data preprocessing

Feature engineering

Model evaluation

Education

Bachelor's degree in CS/EE or related field

Tools

MLflow

Kubeflow

SageMaker

Git

CI/CD

Job description

HUMAN-AI-Z Nexus Technology is seeking an AI Engineer to develop and deploy machine learning models powering core product features. This hybrid role involves collaborating with cross-functional teams to design scalable AI solutions that enhance user experience and operational efficiency.

The ideal candidate will have strong Python, TensorFlow, and PyTorch skills, plus experience with MLOps and cloud platforms.