In this podcast episode, we talked with Nemanja Radojkovic about MLOps in Corporations and Startups.

About the Speaker:

Nemanja Radojkovic is Senior Machine Learning Engineer at Euroclear.

In this event,we’re diving into the world of MLOps, comparing life in startups versus big corporations. Joining us again is Nemanja, a seasoned machine learning engineer with experience spanning Fortune 500 companies and agile startups. We explore the challenges of scaling MLOps on a shoestring budget, the trade-offs between corporate stability and startup agility, and practical advice for engineers deciding between these two career paths. Whether you’re navigating legacy frameworks or experimenting with cutting-edge tools.

1:00 MLOps in corporations versus startups

6:03 The agility and pace of startups

7:54 MLOps on a shoestring budget

12:54 Cloud solutions for startups

15:06 Challenges of cloud complexity versus on-premise

19:19 Selecting tools and avoiding vendor lock-in

22:22 Choosing between a startup and a corporation

27:30 Flexibility and risks in startups

29:37 Bureaucracy and processes in corporations

33:17 The role of frameworks in corporations

34:32 Advantages of large teams in corporations

40:01 Challenges of technical debt in startups

43:12 Career advice for junior data scientists

44:10 Tools and frameworks for MLOps projects

49:00 Balancing new and old technologies in skill development

55:43 Data engineering challenges and reliability in LLMs

57:09 On-premise vs. cloud solutions in data-sensitive industries

59:29 Alternatives like Dask for distributed systems

🔗 CONNECT WITH NEMANJA

LinkedIn -   / radojkovic  

Github - https://github.com/baskervilski

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