Member of Technical Staff, Machine Learning

AboutThere are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal to no prompting. Our first application is an agent-first mobile communication app. We believe building applications that users use daily for communication, coordination and collaboration needs will help integrate AI into their lives. The net effect is to eliminate misinformation, achieve low coordination costs, enable high quality tasks and collaboration at scale with minimal or little prompting.  RoleDevelop and improve ML models for classification, retrieval, ranking and personalisation Build classifiers and ranking models, optimising accuracy, precision, latency and inference cost Improve search relevance and context retrieval using embeddings, hybrid search and reranking Develop personalisation models using user behaviour and product data Build evaluation pipelines, datasets and metrics to measure model quality and detect regressions Train, fine-tune and deploy models using production ML pipelines Monitor model performance, debug production issues and improve models based on evaluation results and user feedback  Requirements3+ years of machine learning engineering experience, including deploying models to production Strong Python programming s