Remote ML Systems Engineer - Production AI Pipelines

YO IT Consulting; Al Ruways Industrial City; On-site; AED 200,880 - 334,800; Full time

Job summary

YO IT Consulting in Abu Dhabi Emirate, United Arab Emirates is seeking an AI Engineer to design production-grade ML models, automate deployment pipelines, and contribute expert technical input used to improve AI systems.

The role combines ML engineering, cloud infrastructure, software development, and container orchestration, requiring Python or Java, AWS, Kubernetes, and CI/CD practices to deliver scalable ML services remotely.

Qualifications

• Proven expertise in machine learning algorithms, model development, and production deployment.
• Strong understanding of supervised, unsupervised, and other relevant ML techniques.
• Professional programming skills in Python or Java.
• Experience contributing to large-scale software engineering projects.
• Strong knowledge of software architecture, testing, version control, and maintainable code development.
• In-depth experience implementing CI/CD workflows.
• Familiarity with AWS for ML apps and data pipelines.

Responsibilities

• Design, develop, test, and optimize machine learning models for production environments.
• Translate complex business and data challenges into practical ML solutions.
• Evaluate real-world data problems and determine suitable modeling approaches.
• Train models and evaluate accuracy, reliability, and scalability.
• Build production-ready ML services that integrate with existing software systems.
• Develop end-to-end ML pipelines and CI/CD workflows.
• Monitor production ML services and investigate performance issues.

Skills

Machine learning

Python

Java

AWS

Kubernetes

Docker

Remote work

Tools

Docker

Kubernetes

Job description

YO IT Consulting in Abu Dhabi Emirate, United Arab Emirates is seeking an AI Engineer to design production-grade ML models, automate deployment pipelines, and contribute expert technical input used to improve AI systems.

The role combines ML engineering, cloud infrastructure, software development, and container orchestration, requiring Python or Java, AWS, Kubernetes, and CI/CD practices to deliver scalable ML services remotely.