Astrolab
FrancePublished: 11 Nov 2026
Predictive Maintenance with Time-Series AI
- Internship
- 4-6 months
- Hybrid
- Paid
- Deadline: 25 Nov 2026
- Software engineering
- Data science
- Artificial intelligence and technology transformation
- Machine learning
- MLOps / DevOps
Job description
Track
Software Engineering — reference SE-04
Project
Develop an AI-based predictive maintenance solution using sensor data and time-series models.
Objectives
- Build a sensor data pipeline with quality checks.
- Train forecasting and anomaly detection models on time-series data.
- Set up MLOps with versioning, deployment and drift alerts.
Candidate profile
Student in software engineering or data science, with solid Python skills and an interest in ML systems.
Skills and tools
- AI-assisted development
- Time-series analysis
- MLOps
The project is part of Astrolab’s PFE Book 2027. Projects have an estimated duration of up to six months, confirmed with the supervisor.