Jobs via Dice is seeking a Machine Learning Engineer to build production-grade machine learning capabilities aimed at enhancing the operations of data centers. The role involves developing models for capacity forecasting, anomaly detection, and sustainability insights, while collaborating with various teams to create measurable ML use cases.
Responsibilities:
- Design, train, evaluate, and deploy ML models for forecasting, anomaly detection, and operational recommendations
- Build reliable data and feature pipelines from OSPI®, telemetry, CMDB, and integration sources
- Operationalize models with monitoring, retraining, versioning, and performance validation
- Partner with Product, Engineering, and Solutions teams to turn customer workflows into measurable ML use cases
- Document model assumptions, evaluation methods, and implementation guidance for internal and external stakeholders
Requirements:
- 4+ years of experience in machine learning engineering, applied ML, or data science with production ownership
- Strong Python skills and experience with common ML libraries/frameworks
- Experience building data pipelines and working with SQL and large-scale structured datasets
- Familiarity with MLOps practices including model serving, monitoring, CI/CD, and reproducibility
- Ability to frame business and operational problems as measurable ML outcomes
- Experience with time-series forecasting, anomaly detection, or data center / infrastructure operations