Advanced Research Engineer

AI & Data Science Engineer

We're seeking an experienced AI & Data Science Engineer with a strong foundation in Python and a growing interest in machine learning, data processing, and intelligent system design. In addition to hands‑on model development and data work, you will contribute to early‑stage system definition, requirements analysis, and integration planning. You will help build AI models, data pipelines, and analytics tools that support decision‑making and system‑level intelligence across multidisciplinary engineering projects.

• Develop ML models for prediction, classification, anomaly detection, and decision support.
• Build and maintain data pipelines for structured, unstructured, and sensor‑derived datasets.
• Implement Python modules for model training, evaluation, and deployment workflows.
• Create simple UI tools using Python frameworks for visualising data, model outputs, and system status.
• Support data engineering tasks including feature extraction, dataset curation, and data quality checks.
• Participate in model optimisation, benchmarking, validation, and documentation.
• Work with senior engineers to elicit, clarify, and document AI‑related requirements.
• Research COTS AI tools, cloud services, and data‑processing technologies for potential integration.
• Contribute to system architecture by defining data flows, module interactions, and integration points.
• Support integration testing and system‑level debugging across data, software, and hardware boundaries.

• Python proficiency with experience in Num Py, Pandas, and scikit‑learn.
• Understanding of ML fundamentals and interest in model development and evaluation.
• Understanding of data pipelines, analytics workflows, and intelligent systems.
• Ability to interpret technical requirements and translate them into actionable tasks.
• Interest in system‑level thinking and multidisciplinary engineering.

• Familiarity with deep learning using Tensor Flow or PyTorch.
• Knowledge of data visualisation and dashboarding tools.
• Experience with system diagrams and interface documentation.
• Exposure to MLOps, CI/CD, or model deployment pipelines.
• Exposure to cloud ML platforms such as Azure ML, AWS Sagemaker, or GCP Vertex AI.
• Experience with Python UI frameworks (Tkinter, PySide, PyQt).

• Strong analytical and problem‑solving mindset.
• Ability to collaborate in cross‑functional engineering teams.
• Clear communication and documentation skills.
• Curiosity about how data, models, and system components interact.

Due to the nature of our business, all employment is subject to satisfactory references being obtained alongside a level of security clearance checks.