Lead the development of AI use-case solution designs, balancing innovation with practicality.
Oversee the entire data science / AI delivery lifecycle, from data exploration to model development/tuning to deployment, monitoring, and performance optimisation using ML and AI Ops best practices.
Lead and work within cross-functional teams comprising of business leaders, product managers, data scientists, data engineers and ML/AI engineers.
Partner with the Responsible AI team to embed robust ethical principles, bias mitigation techniques, and regulatory compliance into all AI development workflows.
Coach and mentor junior data scientists and AI engineers, helping to grow team capabilities and fostering a culture of continuous learning and curiosity.
Maintain an active view of emerging tools and techniques. Develop proof-of-concepts to demonstrate new capabilities. Guide the team in solving complex AI use cases and improving existing approaches.

Extensive experience developing and deploying AI systems and machine learning models in a production environment.
Master’s or PhD (preferred) in Computer Science, Mathematics, Engineering, or relevant STEM field.
Deep knowledge of AI/ML concepts, algorithms, and techniques, including Generative AI, Agentic AI and reinforcement learning.
Strong proficiency in programming languages, particularly Python.
Expertise in AI/ML frameworks such as PyTorch/TensorFlow, Scikit-learn, Statsmodels, LangGraph and ADK.
Familiarity with cloud platforms (preferably Google Cloud Platform and Vertex AI).
Strong analytical, critical thinking, and complex problem-solving abilities.
Excellent communication, interpersonal, and influencing skills, with the ability to convey business information from technical subject matter.
A high degree of ethical awareness, with an understanding of AI ethics, risk mitigation, and bias detection.
Adaptability and a passion for continuous learning to keep up with the rapidly evolving AI landscape.

Lead AI Scientist

Key skills