How to succeed as an ML research scientist in task-oriented dialogue

Task-oriented dialogue, an area of research within the broader field of conversational AI, is an exciting area centered around building dialogue systems to solve tasks. It is a high-impact area of study as natural language systems become increasingly ubiquitous across consumer applications and the enterprise. In addition, researchers in this field get to work on open research questions with high scientific impact. Success as an applied research scientist in this field is largely driven by three main objectives: identifying the computational problem underlying the product goal, defining the right metrics of success, and innovating on the state of the art in the form of published research papers and product impact. We've identified four key ways new researchers can make sure they're preparing themselves to succeed in AI research in industry, particularly in task-oriented dialogue.