Job Description Our customer is seeking a highly experienced Machine Learning / AI Architect (6+ years) to design, develop, and operationalize predictive models that identify track nonconformities across a metropolitan subway system. This role will work within a Google Cloud Vertex AI environment, leveraging multi-modal sensor data (vibration, audio, location) captured via Pixel-based hardware kits on revenue cars, along with ground-truth defect data from MTA's Hexagon (HxGN) system. The ideal candidate will play a critical role in advancing the TrackInspect application by delivering production-grade ML solutions for predictive maintenance and anomaly detection. Key Responsibilities Perform advanced feature engineering on sensor and operational datasets to identify patterns associated with known track defects in HxGN Refactor and enhance existing prototype ML models for pilot and production-scale deployment Utilize Vertex AI Workbench to train, retrain, version, and track ML models, experiments, and performance metrics Conduct hyperparameter tuning, model validation, and optimization to improve nonconformity prediction accuracy Deploy models for daily batch inference, integrating with pipeline-driven sensor data ingestion systems Implement model monitoring, alerting, and feedback loops using Track Inspector inputs within HxGN Design and maintain CI/CD pipelines and multi-environment deployment strategies for ML lifecycle management Build and maintain BigQuery-based prediction views, including location metadata, prediction outputs, and user feedback fields Evaluate model outputs against known defect datasets and present findings in model evaluation sessions with MTA stakeholders Collaborate cross-functionally with engineering, data, and business teams to improve model performance and usability We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.
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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements 10+ years of professional experience in Machine Learning, AI, or Data Science roles 6+ years of Machine Learning Architecture experience 3+ years of AI Architecture/Development experience Strong proficiency in Python (e.g., scikit-learn, TensorFlow, PyTorch) and SQL Hands-on experience with Google Cloud Vertex AI (Workbench, training pipelines, model deployment) Deep understanding of:
- Feature engineering techniques
- Model training and validation frameworks
- Hyperparameter optimization methods Experience designing and deploying production-grade ML systems Experience building data pipelines and CI/CD workflows for ML models