ML Engineering vs ML Research

AI is shaping business and industries in hitherto unforeseen ways. Consequently, there’s a huge demand for machine learning skills across the globe.

As a business, you could have already considered building a machine learning research team. When you consider building an ML team for your business, the next step is to find and recruit those smart scientists with PhDs, and then expect them to deliver the ML magic that can transform your business in a significant way.

The question is: Do you, as a business, need an ML Research team? In most cases, the answer is NO.

ML Research

ML Research is all about research, where you push the boundaries of science, in the field of AI. If you’re developing something really cutting edge, you need an ML Research team, all those MS and PhDs with multiple publications and who can find custom solutions to your problems by extending the current developments in the field of AI even further.

ML Engineering

ML Engineering is all about taking the latest ML research and translating that research into something valuable for the business.

ML engineers are people who are experts at delivering software as a service, or as a product to your customers. These are people who know how to do the necessary plumbing to translate the already available ML research into practice. These are people who are very good with cloud computing services from the likes of Amazon, Microsoft, Google and IBM.

In essence, ML engineers have extensive experience in orchestrating and deploying cutting edge ML solutions from the world’s top AI vendors to solve specific, high impact problems for your business.

Cordiant Technologies is an ML Engineering company.