AI Developer for Industrial AI Applications

Project overview

Automation of the model retraining process

Simulation-based controller optimization

Databricks-based monitoring

Observability & Monitoring for Edge AI

• Further development of the training pipeline
• Integration into Krones support processes
• Development and validation of simulation models for filling processes
• Automated optimization of controller parameters in simulation
• Transfer and validation of the optimized controller parameters on the real test setup in the filling technology laboratory
• Monitoring of data quality, data drifts, and control loop performance
• Expansion of existing monitoring dashboards
• Development of automated notifications for quality and performance deviations
• Collection, visualization, and alerting of metrics and logs
• Setup of real-time monitoring for edge AI services with OpenTelemetry
• Development of monitoring and alerting concepts from the edge to the cloud

Requirements

Work experience :

Not explicitly specified, but list of requirements matches senior profile > 8 years of experience

Project language: German / Documentation: German/English

• Databricks or similar applications
• Docker, Kubernetes
• Edge and cloud applications
• TensorFlow or PyTorch
• Databricks, Data lake and data Lakehouse implementation AWS cloud Services
• Advanced Data Engineering: data modeling, ETL/ELT design, & architecture
• Spark and PySpark
• Python for data engineering
• ML pipeline orchestration and automation
• MLflow or similar
• Terraform / CloudFormation or similar
• Data quality tooling example DQX
• SQL
• Git
• Reinforcement Learning
• AI-assisted programming

Project details

15.11.2026

Project end: 31.03.2027 + ext. 31.12.2027

Utilization:

Place of performance: remote, client locations as per demand

• Proportion remote / onsite mostly remote, approx 3 days/quarter onsite a client location as per indiv. Agreement
• Start: 2026-11
• Duration: 5 Monate
• Location: DE
• Languages: German