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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