[Remote] Machine Learning Engineer

ControlRooms.ai builds an AI troubleshooting platform for heavy industry. In this remote Machine Learning Engineer role, you will own ML training and inference pipelines for time-series anomaly detection and forecasting, deploy models on Azure ML, and ensure reliability at scale. The role requires 3+ years of ML engineering experience with strong Python and MLOps skills.

• Design and build ML training and inference pipelines for time-series prediction (anomaly detection and forecasting)
• Build distributed processing services with Prefect and Ray (Ray Serve on Kubernetes) and package them as FastAPI microservices
• Deploy models for real-time scoring on Azure ML managed online endpoints, including blue/green rollout and autoscaling
• Orchestrate distributed training and batch scoring with Prefect and Azure ML, including parallel hyperparameter search (Optuna)
• Tune Linear Regression, Neural Networks, Tree Methods, and other standard predictive methods
• Tune unsupervised anomaly detection models
• Own model reliability at scale: diagnose and fix production failure modes and harden pipelines
• Build validation rigor: time-series cross-validation/backtesting, champion-challenger comparison, experiment tracking with MLflow
• Implement monitoring, logging, distributed tracing, and alerting (e.g., OpenTelemetry)
• Collaborate across data science, front-end, product, and QA to ship production-ready ML