Senior AI-Powered Predictive Maintenance Engineer (Hybrid)

Novelis; Küsnacht; Hybrid; CHF 120,000 - 170,000; Full time

Benefits offered by this job

Pension scheme

Sabbatical

Hybrid work

Corporate benefits

Fitness subsidies

Training programs

Job summary

Novelis is seeking a Senior Predictive Maintenance Engineer to design, develop, and deploy AI-driven predictive maintenance and asset-reliability solutions across manufacturing operations. The role focuses on reducing downtime and improving equipment reliability in a global aluminum recycling and fabrication network, including the Küsnacht hub in Switzerland.

The ideal candidate holds a Master’s in AI/ML or related field, with 5+ years in AI/ML engineering and hands-on experience with

Qualifications

• Master’s degree or advanced certification in AI, ML, or related field.
• 5+ years of experience in AI/ML engineering, data science, predictive maintenance, reliability analytics, or industrial AI systems delivery.
• Experience in developing predictive models using time-series data, sensor data, or equipment telemetry.
• Proficient in Python and ML frameworks; familiar with IoT and OT data.

Responsibilities

• Develop and deliver components of predictive maintenance and asset-reliability systems.
• Build models for failure prediction, health scoring, remaining-useful-life estimators, and anomaly detection.
• Support scoping and design of industrial AI solutions with Sr. AI Engineer Leader.
• Optimize model performance across training, inference, edge compute, and production stability.
• Contribute to MLOps practices including monitoring, drift detection, retraining, and documentation.

Skills

Python

ML frameworks

Time-series data

Sensor data

Industrial AI

Analytical skills

Problem-solving

Education

Master’s degree in AI/ML

Advanced certification

Tools

MLOps

Deployment tooling

Job description

Novelis is seeking a Senior Predictive Maintenance Engineer to design, develop, and deploy AI-driven predictive maintenance and asset-reliability solutions across manufacturing operations. The role focuses on reducing downtime and improving equipment reliability in a global aluminum recycling and fabrication network, including the Küsnacht hub in Switzerland.

The ideal candidate holds a Master’s in AI/ML or related field, with 5+ years in AI/ML engineering and hands-on experience with