Principal Machine Learning Engineer

Reqiva; Abu Dhabi; On-site; AED 300,000 - 420,000; Part time

Job summary

Reqiva in Abu Dhabi seeks a Principal Machine Learning Engineer to lead enterprise AI initiatives onsite. You will architect scalable ML systems, guide generative and agentic AI projects, and implement robust MLOps with CI/CD.

Requires 10+ years in software/ML and hands-on Python, PyTorch, TensorFlow, Spark, and Azure ML. Strong Kubernetes/Docker experience is essential as is leadership in ML teams.

Qualifications

• 10+ years in software engineering and ML.
• 5+ years delivering production AI/ML solutions.
• Strong Python programming experience.
• Hands-on with PyTorch, TensorFlow and Scikit-learn.
• Experience with Azure ML, Databricks and Apache Spark.
• Strong knowledge of Kubernetes, Docker and CI/CD.
• Experience implementing MLOps frameworks and production ML pipelines.

Responsibilities

• Design scalable ML architectures and pipelines.
• Lead development of predictive, Generative AI and agentic AI solutions.
• Build and optimise model training and inference platforms.
• Establish MLOps practices and CI/CD pipelines.
• Ensure model monitoring, governance and explainability.
• Collaborate with data scientists, architects and eng teams.
• Provide technical leadership and mentorship to ML engineers.

Skills

Python

ML Engineering

MLOps

CI/CD

Production AI

Tools

Azure Machine Learning

Databricks

Apache Spark

PyTorch

TensorFlow

Scikit-learn

Kubernetes

Docker

Job description

Principal Machine Learning Engineer

Location: Abu Dhabi, UAE
Salary: Based on experience
Working Arrangement: Onsite
Employment Type: Contract

The Opportunity

We are seeking an experienced Principal Machine Learning Engineer to lead the development and deployment of enterprise-scale AI and machine learning solutions in Abu Dhabi.

This senior technical role requires strong expertise in Python, Azure Machine Learning, MLOps and modern ML frameworks, with a focus on building scalable, production-grade AI systems.

Key Responsibilities

• Design and develop scalable machine learning architectures and pipelines.
• Lead the development of predictive, Generative AI and agentic AI solutions.
• Build and optimise model training and inference platforms.
• Establish MLOps practices, automation frameworks and CI/CD pipelines.
• Ensure effective model monitoring, governance and explainability.
• Collaborate with Data Scientists, Architects and engineering teams.
• Provide technical leadership and mentorship to ML Engineers.

Required Experience

• 10+ years of software engineering and machine learning experience.
• 5+ years delivering production AI/ML solutions.
• Strong programming experience with Python.
• Hands-on experience with PyTorch, TensorFlow and Scikit-learn.
• Experience with Azure Machine Learning, Databricks and Apache Spark.
• Strong knowledge of Kubernetes, Docker and CI/CD.
• Experience implementing MLOps frameworks and production ML pipelines.
• Strong understanding of scalable ML architectures and model deployment.

Desirable Experience

• Previous experience within financial services or regulated environments.
• Experience developing and deploying Generative AI and agentic AI solutions.