Cognitive Maintenance AI Engineer: Predictive Reliability

SGInnovate; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Hyper-growth path

Leadership tracks

Direct leadership access

Zero bureaucracy

Global data challenges

End-to-end ownership

Career acceleration

Job summary

SGInnovate is seeking an AI Engineer - Cognitive Maintenance to forecast equipment failures, optimize asset reliability, and reduce downtime. You will work with large-scale time-series data and IoT streams, building production-ready models for industrial AI applications.

The role emphasizes collaboration across teams, experimentation with state-of-the-art condition monitoring methods, and translating research into robust, scalable solutions deployed on industrial assets.

Qualifications

• Experience in machine learning, time-series analysis, and anomaly/failure detection.

Responsibilities

• Predictive Maintenance AI Model Development: Design and implement machine learning and deep learning models for Predictive Maintenance applications.
• Data Processing and Analysis: Pre-process sensor data streams to identify patterns that predict equipment failures.
• Deployment and Maintenance: Deploy AI models to production environments and monitor performance.
• Collaboration and Problem Solving: Work with engineers to improve data pipelines and model accuracy.
• Research and Innovation: Stay updated with AI techniques and translate ideas into deployable solutions.
• Performance Monitoring: Develop tools to monitor models in real-time and ensure reliability.
• Documentation and Reporting: Document models and plan IoT hardware deployments at client sites.

Skills

Machine learning

Time-series analysis

Anomaly detection

Problem solving

Communication

Tools

Python

R

Java

TensorFlow

PyTorch

Scikit-learn

AWS

GCP

Azure

Signal processing

Job description

SGInnovate is seeking an AI Engineer - Cognitive Maintenance to forecast equipment failures, optimize asset reliability, and reduce downtime. You will work with large-scale time-series data and IoT streams, building production-ready models for industrial AI applications.

The role emphasizes collaboration across teams, experimentation with state-of-the-art condition monitoring methods, and translating research into robust, scalable solutions deployed on industrial assets.