- Company Name
- Technip Energies
- Job Title
- Internship - AI for Engineering – AI analysis of technical data & prediction F/M
- Job Description
-
Job title: Internship – AI for Engineering (AI analysis of technical data & prediction F/M)
Role Summary:
A six‑month internship for final‑year engineering students focused on developing an AI‑driven prototype that processes and predicts outcomes from engineering technical data (equipment databases, datasheets, P&IDs, specifications, layout plans). Students will gather and structure data, establish consistency rules, apply AI methods (LLMs, vision models, time‑series analysis), build and validate a prediction tool under mentorship.
Expectations:
- Deliver a working prototype that can analyze engineering datasets and provide consistent predictive insights.
- Demonstrate competency in data collection, modeling, and validation workflows.
- Collaborate effectively with cross‑disciplinary teams and contribute to documentation and presentations.
Key Responsibilities:
- Collect, clean, and structure existing engineering technical data.
- Define consistency criteria and recurring pattern identifiers.
- Employ AI tools (Large Language Models, computer vision techniques, time‑series algorithms) to analyze data and generate predictions.
- Develop and iterate on a prototype prediction application.
- Validate predictions against real-world use cases and refine models.
- Coordinate with Information Management, Digital, and Discipline Leads teams.
- Document methodologies, results, and lessons learned.
Required Skills:
- Strong foundation in data science and machine‑learning concepts.
- Proficiency in Python, including data‑processing libraries (pandas, numpy, scikit‑learn) and AI frameworks (PyTorch, TensorFlow).
- Experience applying LLMs, computer‑vision techniques, and time‑series analysis.
- Ability to work with technical engineering data formats and schema.
- Analytical mindset, problem‑solving abilities, and clear communication.
- Team collaboration, openness to mentorship, and self‑direction.
Required Education & Certifications:
- Current enrollment as a final‑year student in Mechanical, Electrical, Industrial, Civil, or related engineering discipline.
- Completed coursework or equivalent experience in data analytics/AI.
- No mandatory certifications required; supplementary data science certifications (Coursera, edX, etc.) considered advantageous.