AI/ML Engineer

About the Role

We are looking for an experienced AI/ML Engineer witha strong background in machine learning and recent hands-on experience in ArtificialIntelligence and Generative AI. The successful candidate will work onbuilding, deploying and supporting AI/ML solutions using the Databricksplatform, collaborating with data, technology and business stakeholdersacross the region.

This role is suited to someone who combines strong MLengineering fundamentals with practical experience in emerging AI technologiesand can translate business requirements into scalable AI solutions.

Key Responsibilities

• Design, develop and deploy scalable Machine Learning and AI solutions using Databricks.
• Develop and productionise ML models across the end-to-end lifecycle, including data preparation, feature engineering, model training, evaluation and deployment.
• Work with Generative AI / LLM technologies to develop practical AI use cases and solutions.
• Build solutions involving RAG, embeddings, vector search, prompt engineering and AI/LLM applications where applicable.
• Develop and optimise data and ML pipelines using Python, PySpark and SQL.
• Utilise MLflow and Databricks ML/AI capabilities for experiment tracking, model management and deployment.
• Collaborate with Data Engineers, Data Scientists, Architects and business stakeholders to deliver production-ready solutions.
• Implement appropriate practices around model monitoring, performance, scalability, security and responsible AI.
• Stay current with emerging developments in AI, GenAI and Machine Learning and assess their applicability to business requirements.
• Support technical discussions and communicate AI/ML concepts effectively to both technical and non-technical stakeholders.
• Work with regional and international teams and stakeholders in a collaborative environment.

Required Skills & Experience

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering or a related discipline.
• 5+ years of experience in Machine Learning, Data Science or AI/ML Engineering.
• Strong hands-on experience with Python and SQL.
• Strong experience with Databricks and modern data/ML platforms.
• Practical experience developing and deploying Machine Learning models in production environments.
• Recent hands-on experience with AI / Generative AI / LLM technologies.
• Understanding of ML lifecycle, MLOps, model deployment and monitoring.
• Experience with MLflow or equivalent ML lifecycle management platforms.
• Good understanding of data processing frameworks such as PySpark.
• Experience with cloud platforms such as AWS, Azure or GCP.