Key Responsibilities
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Lead the end-to-end prototyping lifecycle for data and AI systems, from concept design to Proof-of-Concept development.
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Develop and refine AI prototypes using novel techniques, with emphasis on LLM development, fine-tuning, optimisation, and real-world integration.
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Produce clear, detailed technical documentation for experiments and prototypes.
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Support and run innovation challenge activities to surface new ideas and prototype approaches.
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Contribute technical thought leadership through papers, blogs, and presentations on AI best practices.
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Participate in demos, technical showcases, and internal knowledge-sharing sessions.
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Engage with global research and industry partners to stay current with emerging trends and represent the team at international forums.
Requirements
You should have at least 5 years of experience in two or more of the following domains:
AI Product Engineering / Prototyping
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Translating real-world problems into AI/ML problem statements.
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Building ML/LLM models using modern AI libraries and techniques.
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Deploying AI workflows to enhance product development or operational processes.
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Assessing the effectiveness, scalability, and sustainability of AI workflows.
Data Engineering
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Hands-on experience with data collection, ingestion, storage, transformation, and pipeline design.
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Ability to map complex data sources, design data flows, and integrate multiple streams into usable datasets.
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Familiarity with data management and optimisation practices.
AI Ethics & Governance
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Applying ethical guidelines and governance frameworks in AI development.
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Ensuring responsible and compliant use of AI in projects.
Additional Attributes
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Experience commercialising or translating emerging technologies into practical applications.
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Strong understanding of the practical limitations and challenges in AI and data systems.
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Passion for hands-on experimentation and rapid prototyping.
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Interest or experience in LLM development, model fine-tuning, agentic workflows, or generative AI applications.