Sr ML/AI Engineer

Description: Client is seeking an ML/AI Engineer to develop, fine-tune, and operationalize machine learning models that predict track nonconformities on the NYC subway system. Working within a Google Cloud Vertex AI environment, you will leverage sensor data (vibration, audio, location) captured by Pixel phone hardware kits on revenue cars and ground-truth defect records from MTA’s Hexagon system to build predictive models supporting the TrackInspect application., * Perform feature engineering on sensor and operational data to identify patterns correlated with documented track defects in Hexagon (HxGN)

• Leverage and refactor existing prototype ML models for pilot-scale use; validate performance and suitability for production
• Utilize Vertex AI Workbench to train, retrain, and version ML models; track experiments and metrics
• Conduct hyperparameter tuning and model validation activities to optimize nonconformity prediction accuracy
• Deploy trained models for daily batch inference; connect deployed models to batched sensor input pipelines
• Implement model monitoring, alerting, and a continuous feedback loop from Track Inspector inputs captured in HxGN
• Build and maintain CI/CD pipelines and multi-environment deployment strategy for current models
• Build the BigQuery ‘Predictions - User Friendly View’ incorporating location attributes, prediction metadata, and feedback fields
• Assess model results against known track defects within HxGN and present findings at model evaluation meetings with MTA
• Proficiency in Python (scikit-learn, TensorFlow or PyTorch) and SQL
• Hands-on Vertex AI experience (Workbench, training pipelines, model deployment)

Artificial Intelligence (AI), Predictive Modeling, Fast Food, Artificial Intelligence (AI), Machine Learning, Cloud Computing, MTA, Software Administration, Bug Tracking/Defect Management, Prototyping, * Strong understanding of feature engineering, model validation, and hyperparameter optimization

• Experience with time-series or sensor data (vibration, audio, or accelerometer signals a plus)
• Familiarity with BigQuery as a data platform for ML pipelines
• Experience with geospatial ML or GPS/LRS-based positioning models
• Prior work in predictive maintenance, anomaly detection, or IoT sensor analytics
• Google Professional ML Engineer certification
• Understanding of transit or infrastructure asset management systems
• Experience with Looker Studio or similar BI tools for ML output visualization