3 years ago

Category: Business, machine-learning, artificial-intelligence

For all the technological advancements we are witnessing in AI and machine learning, the practical benefits remain elusive in the non-tech business world, frustrating decision-makers as AI investment climbs. For example, over the past several years, many Fortune 500 companies have invested in strong data science teams and AI labs, but still struggle when it comes to producing and scaling their models.

Enter the cloud AI engineer who, theoretically, would be able to cover all these duties — including knowledge of and experience with the tools and accelerators that cloud platforms now offer, as well as demonstrated aptitude for fast-paced development in AutoML.

The cloud AI engineers of the future will focus on the deployment of AI and ML models at scale in the cloud, and on integrating them with existing products and IT systems.

Obviously, tackling all of these would be a huge undertaking for one individual; given the vast workloads on both the cloud and engineering fronts, it isn’t possible to replace these workers and their skills with just a handful of cloud AI engineers.