Staff Engineer, Process Engineering (Data Analytics)
Summary
Design and deploy AI/ML models to optimize manufacturing processes, build data pipelines, and ensure real-time analytics for industrial automation and edge computing.
- Acquire real time data or batch data via industrial protocols
- Apply Six Sigma for continuous improvement
- Automate manufacturing model coverage
- Build end to end data pipeline
- Calibrate thresholds with guardrails
- Containerize and deploy model inference
- Coordinate IT OT network infrastructure
- Create deployment scripts for production
- Define SOP for model capability drift detection
- Design processing algorithms
- Develop AI ML mathematical models
- Enhance prediction power
- Ensure cybersecurity for model deployment
- Execute model recalibration
- Integrate edge computing units with machine systems
- Integrate with MES interfaces
- Maintain model versioning and configuration management
- Optimize feature extraction
- Perform root cause analysis
- Reduce compute cost
- Reduce inference latency
- Select ML AI techniques
- Troubleshoot algorithmic errors
- Troubleshoot communication issues
- Troubleshoot edge device connectivity
- Troubleshoot inference failures
- Validate AI ML mathematical models