Pointers on AI/ML Career Success

Paritosh Desai (Google Inc.)

While there are many commonalities between academic research and roles in the industry for applied math professionals, there are also important differences. These differences are material in shaping career outcomes in the industry and we try to elaborate on them by focusing on two broad themes for people with academic research backgrounds. First, we will look at the common patterns related to applied AI/ML problems across multiple industries and specific challenges around them. Second, we will discuss emergent requirements for success in the industry setting. We will share principles and anecdotes related to data, software engineering practices, and empirical research based upon industry experiences.