Sr. Machine Learning Engineer
Current• Developed, prototyped, and built a streaming anomaly detection service on top of Flink that uses machine learning modeling to automatically detect anomalies for all golden metric time series (approx. 70 million time series) in the New Relic platform.• Built an automated feedback loop that allows for continuous improvement of anomaly detection models by incorporating user feedback into the training process.• Wrote and presented multiple internal blog posts and sets of documentation detailing both the high-level and technical workings of the anomaly detection service.• Supported all of the services owned and maintained by the anomaly detection team by participating in on-call activities and responding to internal engineering questions.