Programmer (AI/ML) – Operational Digital Twin

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Job Description

Parsons is seeking a Programmer (AI/ML) to support the end-to-end delivery of a large-scale Geospatial Digital Twin programme for a major national infrastructure owner in the Middle East. This multi-year initiative will design, build, and operationalize an Operational Digital Twin platform that integrates geospatial data, real-time IoT/SCADA feeds, asset information, and core enterprise systems to enable data-driven planning, operations, and maintenance. The role will work closely with the Software Development Lead, Data & Architecture team, and a team of international experts, developers, and engineers.

The scope spans discovery and stakeholder engagement, analytical use‑case design, proof-of-concept delivery, implementation of a production-grade environment, post-implementation support, and structured training and knowledge transfer. The Programmer (AI/ML) will help design and implement analytical and machine-learning components, support data preparation and feature engineering, contribute to testing and performance tuning of models and services, and assist in ensuring that AI/ML capabilities are robust, explainable, and aligned with key Digital Twin use cases.

What You’ll Be Doing

• Support the Software Development Lead and Data & Architecture team in designing and implementing AI/ML components for the Operational Digital Twin across discovery, PoC, implementation, and post‑implementation support phases.
• Assist in preparing and transforming data for modelling (including cleaning, joining, aggregating, and feature engineering) using structured, time‑series, and geospatial datasets.
• Develop an AI-powered knowledge and query assistant leveraging large language models and a retrieval augmented generation engine.
• Help develop, train, and validate AI/ML models (e.g. for prediction, classification, anomaly detection, optimisation, or forecasting) using agreed tools, libraries, and frameworks.
• Develop and deploy trained models as scalable services or microservices, integrating them with the Digital Twin platform and upstream/downstream applications and APIs.
• Assist in implementing monitoring, performance tracking, and periodic retraining processes for models, and in troubleshooting issues related to data drifts, accuracy, or stability.
• Help document AI/ML components, including data assumptions, model choices, limitations, and usage guidelines, and support knowledge transfer and handover to client and operations teams.
  
  
  

What Required Skills You’ll Bring

• Degree in computer science, data science, engineering, mathematics, or a related technical discipline from an accredited institution.
• Experience developing AI/ML solutions using languages and libraries such as Python, Pandas, NumPy, scikit-learn, and deep learning frameworks (e.g., TensorFlow and PyTorch).
• Working knowledge of core machine‑learning concepts (feature engineering, model selection, training/validation, overfitting, evaluation metrics) and basic statistics.
• Experience with data preparation and handling of large or complex datasets, ideally including time‑series, sensor, or geospatial data.
• Familiarity with geospatial platforms (e.g., Esri ArcGIS) and using spatial data as features in analytical models.
• Exposure to deploying models to production (e.g., as APIs, batch jobs, or streaming components) and to integrating them with applications or data platforms.
• Experience working within multidisciplinary, multinational teams across multiple time zones.
• Strong organisational and coordination skills, with some experience in structured project or delivery environments (e.g., PMI, PRINCE2, Agile/Hybrid).
• Exposure to testing, acceptance, or go‑live activities for analytical or data‑driven solutions.
• Excellent communication and documentation skills, with the ability to clearly explain data, models, and results to non‑technical stakeholders.
• Fluency in spoken and written English; Arabic language skills are a strong advantage.
  
  
  

What Desired Skills You’ll Bring

• Prior work with national infrastructure owners, transport authorities, utilities, or public works organisations.
• Experience applying AI/ML in Digital Twin, smart city, asset management, or operations optimisation contexts.
• Experience working with cloud platforms (e.g., Azure, AWS) and modern data/ML tooling (e.g., MLflow, Databricks, Azure ML, or similar).
• Professional certifications in data science, machine learning, or cloud data/AI services.
  
  
  

Parsons equally employs representation at all job levels no matter the race, color, religion, sex (including pregnancy), national origin, age, disability or genetic information.

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