Machine Learning Engineering in Finance - Nemanja Radojkovic

We talked about:

• Nemanja’s background

• When Nemanja first work as a data person


• Typical problems that ML Ops folks solve in the financial sector


• What Nemanja currently does as an ML Engineer


• The obstacle of implementing new things in financial sector companies


• Going through the hurdles of DevOps


• Working with an on-premises cluster


• “ML Ops on a Shoestring” (You don’t need fancy stuff to start w/ ML Ops)


• Tactical solutions


• Platform work and code work


• Programming and soft skills needed …

companies data devops engineer engineering finance financial financial sector machine machine learning ml engineer ml ops on-premises ops person sector solve through work