AI/ML Researcher

AI/ML Researchers explore and develop cutting-edge algorithms to push the boundaries of artificial intelligence and machine learning. Their work blends deep theoretical knowledge with experimental analysis, contributing to both academic advancement and real-world innovation in AI technologies.

Expertise Areas

• Algorithm Design – Creating novel machine learning and deep learning architectures for complex tasks
•  Theoretical Research – Applying mathematical and statistical theory to advance understanding of AI systems
•  Experimental Evaluation – Designing experiments to test model performance, generalisability, and robustness
•  Natural Language Processing / Computer Vision / Reinforcement Learning – Specialising in key subfields of AI
•  Publication & Dissemination – Sharing findings through academic papers, conferences, and internal knowledge sharing
•  Collaboration with Engineering Teams – Translating research breakthroughs into scalable, real-world applications

Key Responsibilities

• Developing Novel Models – Research and implement new techniques in machine learning, AI, or related areas
• Advancing the State of the Art – Push the boundaries of what’s possible in areas like generative models, transformers, or self-supervised learning
• Publishing and Presenting – Contribute to peer-reviewed journals, conferences (e.g., NeurIPS, ICML, ACL), and industry research initiatives
• Evaluating Model Performance – Rigorously test models for accuracy, efficiency, and fairness
• Prototyping and Experimentation – Build proof-of-concept systems and refine them through experimentation

For more information on careers within the field of Data Science visit the jobs board.