Wind-Centric AI Architect: Computer Vision Leader

GE Vernova, Inc.; South Carolina; On-site; USD 113,000 - 189,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

401(k) with company match

Tuition assistance

Paid holidays

Parental leave

Job summary

GE Vernova is seeking a Senior AI Architect for Computer Vision to lead the Wind Engineering Center of Excellence. You will establish shared frameworks for acquisition, labeling, training, evaluation, deployment, and monitoring across engineering initiatives, driving reusable patterns and governance for robust visual intelligence solutions.

You will guide imaging strategy, data acquisition/annotation, and develop 2D/3D, multimodal, and edge/cloud deployments, ensuring measurable inspection

Qualifications

• Minimum 8 years experience with data science and ML/DL in complex environments.
• Experience with Python and common data science frameworks (Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow, XGBoost).
• Experience with time-series or industrial data; temporal validation and non-stationarity.

Responsibilities

• Lead the Computer Vision Center of Excellence for Wind Engineering, setting standards and reusable patterns.
• Define dataset governance, labeling taxonomies, and data leakage prevention.
• Establish model development and validation standards with clear metrics.
• Architect 2D/3D/Multimodal and Spatial AI solutions with robust uncertainty management.
• Design human-in-the-loop workflows and escalation paths for high-consequence observations.

Skills

Python

Data science frameworks

PyTorch

TensorFlow

XGBoost

Time-series data

Statistics

Model evaluation

Education

Bachelor's degree in Data Science, Statistics, Computer Science, Applied Mathematics, Engineering, OR Operations Research

Advanced degree preferred

Tools

Pandas

NumPy

Scikit-Learn

PyTorch

TensorFlow

XGBoost

Job description

GE Vernova is seeking a Senior AI Architect for Computer Vision to lead the Wind Engineering Center of Excellence. You will establish shared frameworks for acquisition, labeling, training, evaluation, deployment, and monitoring across engineering initiatives, driving reusable patterns and governance for robust visual intelligence solutions.

You will guide imaging strategy, data acquisition/annotation, and develop 2D/3D, multimodal, and edge/cloud deployments, ensuring measurable inspection