About the Position

We are looking for a Data & AI Engineer specializing in machine and sensor data intelligence to design, build, and deploy advanced AI solutions for predictive maintenance, anomaly detection, and process optimization. This role focuses on production-grade industrial AI, turning high-frequency machine data into reliable insights that improve uptime, stability, and overall equipment effectiveness (OEE) across Rosenberger’s global manufacturing operations.

Responsibilities

Predictive Maintenance & Reliability

Design and deploy predictive maintenance solutions using machine and sensor data
Model equipment degradation, early failure indicators, and remaining useful life (RUL)
Reduce unplanned downtime through data-driven maintenance strategies

Anomaly Detection & Process Intelligence

Develop anomaly detection models for:
- Machine behavior deviations
- Process instability and drift
- Sensor faults and data quality issues
Build AI models for process monitoring and optimization
Identify root causes of quality and throughput losses using machine data

Machine Data & AI Engineering

Work with high-frequency time-series data from:
- PLCs
- Sensors
- Industrial controllers and machines
Design and implement scalable data pipelines from shop-floor systems to analytics and AI platforms
Apply modern ML and deep learning approaches to sensor and machine data
Integrate AI models into operational workflows and production systems

Deployment & Collaboration

Collaborate closely with:
- Automation and controls engineers
- Production and maintenance teams
- IT and data platform teams
Support deployment of AI solutions in real production environments, including edge and near-real-time use cases
Contribute to standards, reusable components, and best practices within the Data & AI Competence Center

Requirements

Bachelor’s or Master’s degree in:
- Engineering
- Computer Science
- Data Science
- or a related technical field
5+ years of experience working with machine data, IoT, or industrial AI
Strong hands-on experience with:
- Python for industrial AI and data processing
- Modern machine learning and deep learning frameworks (PyTorch preferred)
Proven experience with:
- Predictive maintenance
- Anomaly detection
- Process monitoring or optimization
Deep understanding of:
- Time-series data characteristics
- Sensor data quality issues
- Equipment and process behavior in manufacturing
Experience integrating data from industrial systems (PLCs, historians, machine controllers)

Modern Technical Focus (Not Legacy-Only)

Machine learning and deep learning for time-series and sensor data
Unsupervised and semi-supervised learning for anomaly detection
Sequence models and representation learning for machine behavior
Feature learning from raw sensor signals
Model robustness in noisy, incomplete industrial data

Strongly Preferred / Key Differentiators

Hands-on experience with industrial data connectivity, such as:
- OPC UA
- MQTT
- Industrial data historians
Experience deploying AI models in:
- Edge environments
- Near real-time production systems
Knowledge of:
- Condition monitoring
- Reliability engineering concepts
- OEE and process KPIs
Experience with process optimization using machine data
Familiarity with MES, SCADA, or manufacturing IT landscapes

Nice to Have

Experience with cloud-based industrial data platforms
Knowledge of:
- Digital twins
- Simulation-based optimization
Familiarity with MLOps for industrial AI
Experience working in high-mix, high-precision manufacturing

We Offer

Opportunity to build and shape Rosenberger’s Data & AI Competence Center in India
Work on high-impact, real manufacturing problems, not PoCs only
Strong collaboration with German HQ and global production sites
Long-term technical ownership and growth into Lead / Architect roles

Share your updated resumes to [email protected]

Data & AI Engineer – Machine Data Intelligence (Predictive Maintenance & Anomaly Detection)

Job description