[Remote] Machine Learning Engineer

Sourced from flexgen.zya.me

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)