Head of Data & AI (Contractual)
Location: Dubai, UAE
Role Type: Contractual
About the Role:
We are seeking a highly skilled and hands-on Head of Data & AI to lead our initiatives from the front. This is not a purely managerial role; we need a technical leader who is deep in the code, architecture, and strategy. You will be the driving force behind building, fine-tuning, and deploying cutting-edge data pipelines and AI models, with a significant focus on creating practical, agentic AI solutions.
The ideal candidate is a true pioneer—someone who thrives in a fast-paced, unstructured environment and is genuinely passionate about the latest breakthroughs in AI. If you have built Small Language Models (SLMs) from the ground up, live and breathe the MLOps lifecycle, and are eager to experiment with the newest research, we want to hear from you.
Key Responsibilities:
- Technical Leadership & Hands-On Development: Architect, code, and deploy robust data engineering pipelines and machine learning models. You will be directly responsible for the end-to-end delivery of AI solutions.
- Agentic AI & Model Innovation: Lead the design and implementation of agentic AI systems. Drive projects involving the fine-tuning, training, and deployment of foundation models, including SLMs and Large Language Models (LLMs).
- Full-Spectrum MLOps: Build and maintain our MLOps framework to ensure scalable, reproducible, and monitored model training and deployment across cloud environments (Azure, OCI, or AWS).
- Technology & Research Scouting: Proactively explore, evaluate, and integrate the latest AI tools, open-source models (from Hugging Face, etc.), and research papers to keep our stack at the forefront of technology.
- Strategy in Execution: Translate business objectives into a clear, executable technical roadmap for Data & AI, prioritizing high-impact projects that deliver tangible value.
Who You Are:
- You are a builder and an engineer first, with a proven track record of shipping production-level AI/ML systems.
- You have deep, hands-on expertise in Python, TensorFlow/PyTorch, and the Hugging Face ecosystem.
- You have direct experience in building, fine-tuning, or deploying language models (e.g., T5, GPT-like architectures, or custom SLMs). Experience with the OpenAI ecosystem is a strong plus.
- You are fluent in cloud infrastructure (Azure, OCI, or AWS) and modern MLOps tools for CI/CD, experiment tracking, and model serving.
- You are genuinely curious and experimental—you read research papers, tinker with new libraries, and are excited to test novel approaches to solve complex problems.
- A true self-starter who requires minimal direction and can create structure and momentum in ambiguous, high-speed environments.
Required Skills & Qualifications:
- Demonstrable hands-on experience in data engineering, machine learning, and AI.
- Proficiency in Python and core ML frameworks (TensorFlow or PyTorch).
- Practical experience with the Hugging Face ecosystem and transformer models (T5, BERT, etc.).
- Proven experience in the full lifecycle of model development: training, fine-tuning, evaluation, and deployment.
- Solid understanding of cloud platforms (Azure, OCI, or AWS) and their AI/ML services.
- Experience setting up and maintaining MLOps pipelines.
How to Apply:
Please submit your application, including your CV and a link to your GitHub/portfolio. In your application, highlight a specific project where you built, fine-tuned, or deployed a language model or a complex AI agent. We are excited to see what you have created.
Why this JD works:
- Clear Role Definition: It immediately establishes that this is a hands-on, technical leadership role, not a remote people-manager position.
- Targets the Right Profile: The language ("builder," "pioneer," "experimental") is designed to resonate with the curious, skilled engineers you're seeking.
- Highlights Key Technologies: It clearly lists the required tech stack (Python, TF/PyTorch, Hugging Face, Clouds).
- Emphasizes the "What": The responsibilities and "Who You Are" section explicitly mention building SLMs, fine-tuning, agentic AI, and keeping up with research.
- Strong Call to Action: The application instruction filters for serious candidates by asking for specific project details.
