[Hiring] Machine Learning / AI Engineer @Yale University

Role Description

We are seeking a Machine Learning / AI Engineer to develop data-driven solutions supporting asset management, predictive maintenance, fleet operations, and maintenance planning. The ideal candidate will have strong hands-on experience in Python, machine learning, data analytics, and enterprise data environments. Experience with asset management, fleet maintenance, or transportation systems is highly preferred.

• Develop and implement machine learning and AI solutions for predictive maintenance, asset failure prediction, anomaly detection, forecasting, and asset performance optimization.
• Analyze work order, asset, maintenance, and operational data to identify trends, failure patterns, and improvement opportunities.
• Develop models and analytics supporting condition-based maintenance and asset replacement decisions.
• Develop forecasting models to support maintenance and operational decision-making.
• Build and integrate data pipelines and AI/ML solutions with enterprise applications, databases, APIs, and reporting platforms.
• Evaluate model performance and translate analytical results into actionable recommendations for business and maintenance teams.
• Collaborate with EAM functional and technical teams to develop and implement AI/ML solutions aligned with asset management and maintenance requirements.

Qualifications

• 4+ years of experience in Machine Learning, AI, Data Science, or a related field.
• Strong hands-on experience with Python and SQL.
• Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.
• Experience with data preparation, feature engineering, model development, validation, and deployment.
• Strong understanding of machine learning algorithms, predictive analytics, and model evaluation.
• Experience working with databases, APIs, and enterprise data environments.