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Principal AI/ML Engineer

Insight • United Arab Emirates
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AI Summary

Lead technical design, development, and deployment of enterprise-grade AI/ML solutions across the full lifecycle. Provide mentorship, establish engineering standards, and embed responsible AI principles. Requires extensive production experience with Python, PyTorch/TensorFlow, and MLOps practices.

Key Highlights
Technical leadership for enterprise AI/ML solutions from discovery to production
Mentorship and capability development for engineering teams
Establishment of AI/ML architecture standards and responsible AI principles
Expertise in MLOps, CI/CD, and model lifecycle management
Key Responsibilities
Lead the design, development and deployment of scalable AI/ML solutions, taking ownership of the full lifecycle from discovery and experimentation through to production delivery and continuous improvement.
Define and govern AI/ML architecture, engineering standards and best practices, ensuring solutions are secure, maintainable, cost-effective and aligned with wider business and technology strategies.
Drive the adoption of MLOps practices, including CI/CD, model versioning, monitoring, observability, performance optimisation and lifecycle management.
Provide technical leadership and mentorship to engineers, supporting capability development, design reviews, knowledge sharing and the adoption of engineering best practices.
Lead technical discovery activities, proof-of-concepts and architecture assessments, helping shape AI strategy and identify opportunities where AI can improve business outcomes.
Ensure robust documentation, governance and responsible AI principles are embedded throughout the delivery lifecycle, supporting transparency, compliance and operational excellence.
Technical Skills Required
Python PyTorch TensorFlow MLOps
Benefits & Perks
Hybrid work model
Visa sponsorship available

Job Description


Role: Principal AI/ML Engineer

Salary: DOE

Location: Abu Dhabi HQ - Hybrid Model

For international candidates open to relocation, support is available


Role Overview

We are looking for a Principal AI/ML Engineer to provide technical leadership across the design, development, deployment and continuous improvement of enterprise-grade AI and machine learning solutions.


The Principal AI/ML Engineer will work closely with data scientists, software engineers, cloud engineers, architects, product teams and senior stakeholders to translate complex business problems into scalable, secure and measurable AI/ML solutions. The role will also play a key part in mentoring engineers, improving delivery practices, and embedding responsible AI and robust engineering principles across projects.


Key Responsibilities:

  • Lead the design, development and deployment of scalable AI/ML solutions, taking ownership of the full lifecycle from discovery and experimentation through to production delivery and continuous improvement.
  • Define and govern AI/ML architecture, engineering standards and best practices, ensuring solutions are secure, maintainable, cost-effective and aligned with wider business and technology strategies.
  • Design, build and optimise machine learning, deep learning and generative AI solutions, selecting the most appropriate tools, frameworks and approaches to solve complex business challenges.
  • Drive the adoption of MLOps practices, including CI/CD, model versioning, monitoring, observability, performance optimisation and lifecycle management.
  • Collaborate closely with business stakeholders, product teams, architects, data engineers and software engineers to translate requirements into practical AI-driven solutions that deliver measurable value.
  • Provide technical leadership and mentorship to engineers, supporting capability development, design reviews, knowledge sharing and the adoption of engineering best practices.
  • Lead technical discovery activities, proof-of-concepts and architecture assessments, helping shape AI strategy and identify opportunities where AI can improve business outcomes.
  • Ensure robust documentation, governance and responsible AI principles are embedded throughout the delivery lifecycle, supporting transparency, compliance and operational excellence.
  • Stay current with emerging AI technologies, frameworks and industry trends, evaluating their potential application and guiding the organisation's adoption of new capabilities


Required Experience:

  • Extensive experience delivering AI/ML solutions in production environments.
  • Strong Python expertise and experience with frameworks such as PyTorch, TensorFlow and Scikit-learn.
  • Deep understanding of machine learning, deep learning and Generative AI technologies.
  • Experience with Azure, AWS or GCP.
  • Strong knowledge of MLOps, CI/CD, testing and software engineering best practices.
  • Proven experience leading technical teams and influencing architecture decisions.



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