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

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.

Key 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

Required Qualifications

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

What 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 IndiaCareers@rosenberger.in