Staff Machine Learning Engineer — SROT AI
Architected an end-to-end machine learning and business intelligence platform for predictive maintenance and anomaly detection across robot fleets. Built ML pipelines from real-time telemetry ingestion through feature engineering, model training, and model serving. Established MLOps best practices including experiment tracking and CI/CD to support iterative model deployment. • Ingested real-time telemetry streams via Kafka and engineered features • Developed serving endpoints for inference and operational BI dashboards • Built analytics visualization for robot telemetry KPIs and model outputs • Implemented MLflow/W&B tracking and CI/CD using GitHub Actions to reduce deployment cycle time