AI Data Engineer (REF: SDA)
Summary
Build AI/ML models to optimize water and wastewater treatment, using predictive analytics and digital twins to improve efficiency and maintenance.
- Develop AI and machine learning models for water and wastewater treatment applications.
- Build predictive models to optimise treatment performance, asset reliability, and operational efficiency.
- Analyse large operational datasets generated from water treatment facilities and industrial processes.
- Support the development of digital twin and process simulation capabilities.
- Create data-driven solutions for process monitoring, anomaly detection, and predictive maintenance.
- Design and implement algorithms for intelligent process optimisation and chemical dosing.
- Support the deployment of AI applications and analytics platforms.
- Participate in technology development, innovation initiatives, and product roadmap planning.
- Translate technical findings into practical recommendations for clients and stakeholders.
Requirements
- MPhil /PhD in Environmental Engineering or related discipline.
- Bachelor Degree holder from disciplines such as chemical engineering, chemistry, environmental management, environmental science, environmental engineering.
- Experience developing Machine Learning, Artificial Intelligence, or Advanced Analytics solutions.
- Experience working with predictive modelling and optimisation techniques.
- Understanding of water treatment / sewage water treatment processes, engineering systems, or operational technologies.
- Ability to manipulate, analyse, and interpret large datasets.
- Excellent communication skills and ability to work within multidisciplinary teams.
- Strong problem-solving mindset with an interest in applying AI to real-world engineering challenges.