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 to be an ML Engineer
The challenges of transitioning from and electrical engineering and sales to ML Ops
The ML Ops tech stack for beginners
Working on projects to determine which skills you need

Links:

LinkedIn: https://www.linkedin.com/in/radojkovic/

Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Machine Learning Engineering in Finance - Nemanja Radojkovic