Senior Process Optimisation Engineer

Role Overview

We are seeking a Senior Process Optimisation Engineer with strong expertise in industrial water and wastewater treatment, process modelling, mathematical simulation and AI-driven optimisation.

The ideal candidate will combine deep water process engineering knowledge with hands-on programming, computational modelling and applied AI capabilities. This role will involve developing and deploying intelligent digital solutions, predictive models, digital twins and optimisation algorithms to improve the efficiency, reliability and sustainability of industrial water and wastewater treatment operations.

We are looking for an AI-native engineer who actively leverages AI-assisted development tools, understands how to build AI-enabled applications and can translate complex engineering challenges into computational and digital solutions.

Key Responsibilities

1. Water & Wastewater Process Engineering

• Develop and optimise treatment processes involving RO, UF, NF, MBR, biological treatment, desalination and industrial wastewater recovery.

• Analyse plant performance, identify process inefficiencies and recommend improvements in energy, chemical consumption, water recovery and treatment efficiency.

• Perform mass balance, hydraulic calculations, process analysis and root cause investigations.

• Establish process performance KPIs and validate operational improvements.

2. Process Modelling & Digital Twins

• Develop, calibrate and validate mathematical, mechanistic, data-driven and hybrid process models.

• Build digital representations of water and wastewater treatment processes to simulate plant behaviour under varying operating conditions.

• Perform scenario modelling, sensitivity analysis, simulation and process optimisation.

• Integrate process models with real-time operational data to enable predictive monitoring and optimisation.

• Translate engineering principles into computational models and deployable digital solutions.

3. AI, Programming & Computational Engineering

• Develop programming-based solutions for process modelling, simulation, optimisation and predictive analytics.

• Use Python as a core programming tool, including libraries such as NumPy, Pandas, SciPy and scikit-learn.

• Apply machine learning, statistical modelling and AI techniques to solve water treatment and process optimisation problems.

• Develop and implement AI-assisted predictive models, optimisation algorithms and intelligent process control solutions.

• Leverage LLMs, AI coding assistants and agentic development tools to accelerate engineering workflows, modelling and software development.

• Work with APIs, data pipelines and software interfaces to integrate engineering models with digital platforms.

• Write, test, debug and maintain production-quality code for engineering and optimisation applications.

4. Digital Product & Cross-functional Collaboration

• Collaborate with data scientists, AI engineers, software developers and automation teams to develop digital water solutions.

• Translate process engineering requirements into technical specifications, algorithms and software features.

• Support integration of SCADA, PLC, historian and IoT data into digital optimisation platforms.

• Participate in customer deployments, pilot testing, model validation and continuous improvement of digital solutions.