Summary
✨ AI‑Generated
Join an engineering team developing digital-twin capabilities for complex wastewater treatment operations. As a senior Python engineer, you will create physics- and chemistry-based first-principles models, translate engineering equations and process kinetics into computational models, and build clean, modular, scalable software. You will collaborate closely with process engineers, data scientists, and operations teams to enable optimisation, forecasting, and operational decision support.
Highlights
Senior engineering opportunity focused on building sophisticated digital-twin capabilities for complex industrial processes. The role combines scientific modelling with robust software engineering and close collaboration with engineering, data, and operations specialists to support optimisation, forecasting, and better operational decisions.
Description
The Role
Senior Python Engineer with expertise in mechanistic modelling and first-principles simulation to design and build digital twin capabilities for sewage treatment sites.
This role focuses on developing physics and chemistry based models of wastewater processes (e.g.
primary treatment, secondary treatment, tertiary treatment) and implementing them in robust, scalable Python code.
work closely with process engineers, data scientists, and operations teams to create high-fidelity models that enable optimisation, forecasting, and operational decision support
.
Your responsibilities: (Up to 10, Avoid repetition)
Mechanistic Model Development
Develop first-principles models of wastewater treatment processes (e.g., activated sludge kinetics, primary sedimentation).Translate process design equations, mass balances, and kinetics into computational models.Implement models of hydraulics, biological reactions, and process control systems.Python Engineering
Build clean, modular, and well-tested Python code for simulation and optimisation.Ensure code is production-ready with version control, testing, and documentation.Digital Twin Development
Integrate mechanistic models into a real-time digital twin framework.Combine sensor data (e.g., flow rates, DO, ammonia levels) with simulations.Enable features such as:Scenario simulationPredictive forecastingProcess optimisationData Integration & Calibration
Use sensor data to calibrate and validate models.Implement parameter estimation and uncertainty analysis.Work with historians (e.g., SCADA systems) and data pipelines.Collaboration
Partner with:Process engineers (domain expertise)Data scientists (hybrid modelling/ML integration)Operations Team (End User)Communicate complex modelling results to non-technical stakeholders.
Your Profile
Essential skills/knowledge/experience: (Up to 10, Avoid repetition)
Technical Expertise
Strong Python development experience (5+ years preferred).Proven experience with mechanistic / physics-based modelling.Solid understanding of:Differential equations and numerical methodsMass & energy balancesReaction kineticsDomain Knowledge (at least one of the following)
Wastewater/sewage treatment processesEnvironmental engineeringChemical/bioprocess engineeringProcess systems engineeringTools & Libraries
Scientific Python stack/Simulation: NumPy, SciPy, pandasModelling/optimisation: Pyomo, CasADi, Swarm Optimisation or similarVisualisation: Matplotlib, PlotlyVersion control: Git
Preferred Experience
10+ years of experience in Python , mechanistic modelling, or Digital Twin roles.Proven experience Python Modules.Experience in Utilities, Water, Energy, Manufacturing, or Infrastructure sectors.Experience delivering Digital Twin, Asset Intelligence, Smart Operations, or IoT transformation initiatives.
Desirable skills/knowledge/experience: (As applicable)
Desirable Skills
Experience with wastewater modelling frameworks (e.g., ASM models, STOAT)Knowledge of digital twin architecturesExperience integrating ML with mechanistic models (hybrid modelling)Familiarity with cloud platforms (Azure/AWS) and data pipelinesReal-time systems or industrial IoT experience
Key Attributes
Strong problem-solving and analytical thinkingAbility to translate real-world processes into mathematical modelsComfortable working across disciplines (engineering + software + data)Attention to detail and commitment to model accuracy
