Engineering Intern

About the Role

We are looking for a proactive, detail-oriented Process Engineering Intern to support PAMSIMS, an AI-powered platform that automates the interpretation and extraction of engineering information from Piping and Instrumentation Diagrams (P&IDs). Working with process engineers and AI developers, the intern will help prepare training datasets, test model outputs, identify discrepancies and improve platform accuracy and reliability.

Key Responsibilities

• P&ID interpretation: Review drawings to identify process equipment, piping, valves, instruments, control loops, tags and connectivity.
• Training data preparation: Annotate, classify, organise and quality-check engineering datasets used to train and evaluate AI models.
• AI testing and validation: Compare AI-generated outputs against source P&IDs, record accuracy, and identify missing or incorrect information.
• Engineering quality assurance: Flag tag omissions, misidentified symbols, incorrect equipment/instrument classifications and connectivity errors.
• Functional testing and feedback: Execute test cases, maintain issue logs and communicate clear, structured findings to developers.
• Process engineering support: Help develop engineering rules, standardised datasets, validation checklists and practical test scenarios.
• Continuous improvement: Proactively recommend ways to improve data quality, workflows and the usability of PAMSIMS.

Requirements

• Education: Currently pursuing a bachelor’s or master’s degree in Chemical Engineering, Process Engineering or a related discipline.
• Engineering fundamentals: Basic understanding of PFDs, P&IDs, common process equipment, piping components and instrumentation symbols.
• Working style: Strong attention to detail, analytical problem-solving, self-initiative and willingness to learn.
• Collaboration: Ability to document findings clearly and work effectively with engineering and software teams.

Preferred qualifications: Exposure to ISA/P&ID drawing conventions, Excel, Python, data annotation or software testing is an advantage, but not essential. AI programming experience is not required.

What you will gain

• Hands-on experience applying AI to process engineering, interpreting real engineering drawings, validating AI outputs and collaborating across engineering and technology disciplines on an emerging industrial solution.