Job Description Summary

Job Description

Key Responsibilities:

• Solution Architecture: Design end-to-end AI/ML architectures that integrate with existing fleet monitoring systems, turbine data, and legacy system of record databases.
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• Deployment & Scaling: Oversee the transition of models from pilot to production-scale deployment, delivering solutions with high availability, data security, and interoperability across global sites.
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• Technical Leadership: Serve as the primary AI technical point of contact for Fleet Performance stakeholders, guiding best practices in data pipeline development, MLOps, and model governance.
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• Collaborate: Develop AI resource network within GEV Engineering, across GEV/Wind, and external stakeholders to stay aligned on latest methodologies and industry benchmarks.

Required Qualifications:

• Bachelor’s or Master’s degree in Engineering, Computer Science, or Data Science or equivalent experience
  
• Significant experience in AI/ML model development within industrial, energy, or manufacturing sectors.
  
• Proven track record of designing solutions for large-scale, time-series data environments.
  
• Strong understanding of fleet operations, asset management, or reliability engineering.
  
• Proficiency in cloud architecture (e.g., AWS, Azure) and modern MLOps frameworks.

Additional Information