Data Scientist – AI & Machine Learning | Abu Dhabi, UAE

Location: Abu Dhabi, United Arab Emirates
Job Category: Information Technology (IT) & Software; Science & Research
Contract Duration: 3 Months
Experience Required: 5–7 years minimum in AI and Machine Learning engineering
Eligibility: Open to all

Job Overview

An opportunity is available for an experienced Data Scientist to work on AI and Machine Learning initiatives in Abu Dhabi, UAE, under a three-month contract. The ideal candidate will have strong practical experience in AI and Machine Learning engineering, with a proven ability to deploy end-to-end machine learning solutions into production, from data collection through to end-user deployment.

The role requires advanced knowledge of statistics, Machine Learning, and Deep Learning, alongside strong Python programming skills and experience with frameworks such as TensorFlow and PyTorch. Candidates should understand Retrieval-Augmented Generation (RAG) and Model Context Protocol (MCP) principles, as well as modern MLOps and DevOps practices.

The successful candidate should also be capable of designing robust algorithms and data architectures for critical systems, participating in client-facing technical workshops, and working within environments that require careful attention to data security, privacy, and sovereignty.

Key Responsibilities

• Develop and deploy end-to-end Machine Learning solutions, from initial data collection to production and end-user deployment.
• Design robust algorithms and data architectures for critical systems and real-time operational requirements.
• Apply statistical methods, Machine Learning algorithms, and Deep Learning techniques to solve technical problems.
• Work with Python and AI frameworks such as TensorFlow and PyTorch.
• Apply knowledge of RAG and MCP principles to relevant AI engineering solutions.
• Work with databases and SQL, including exposure to NoSQL systems.
• Use MLOps tools such as MLflow to support the development and deployment lifecycle.
• Apply GitLab, Docker, CI/CD, and DevOps tooling within development workflows.
• Participate in or lead client-facing workshops and technical ideation sessions.
• Follow relevant data security, privacy, and sovereignty requirements for defense or critical infrastructure environments.
• Use Jira and Agile practices to support project coordination and delivery.

Required Qualifications and Technical Skills

AI and Machine Learning Engineering

• Minimum 5–7 years of practical AI and Machine Learning engineering experience.
• Proven experience deploying end-to-end ML solutions into production.
• Ability to design algorithms and data architectures for critical systems and real-time operational constraints.
• Experience participating in or leading client-facing workshops and technical ideation sessions.

Technical Expertise

• Advanced knowledge of statistics, Machine Learning, and Deep Learning algorithms.
• Hands-on understanding of RAG and MCP principles.
• Strong proficiency in Python.
• Experience with TensorFlow and PyTorch.
• Solid understanding of database technologies and SQL, with exposure to NoSQL.
• Practical experience with MLflow and MLOps workflows.
• Experience with GitLab, Docker, CI/CD, and modern development environments.
• Familiarity with data security, privacy, and sovereignty requirements in defense or critical infrastructure environments.

Mandatory Tools and Practices

• Hands-on experience with Jira.
• Agile methodologies.
• CI/CD and DevOps practices.
• Git, Jenkins, Artifactory, and Sonar.

Additional Advantage

Exposure to Java, Spark, or Scala is an advantage.

Contract Details

• Position: Data Scientist
• Location: Abu Dhabi, UAE
• Duration: 3 months
• Eligibility: Open to all

Salary, benefits, and the application deadline have not been specified in the supplied vacancy details.

How to Apply

Interested candidates should send their updated CV to:

Email

Subject: Data Scientist

Please highlight your AI and Machine Learning engineering experience, production deployment projects, Python expertise, RAG/MCP knowledge, and relevant MLOps and DevOps tools in your CV.