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MLOps in Corporations and Startups - Nemanja Radojkovic

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Manage episode 471379213 series 2831626
Content provided by DataTalks.Club. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by DataTalks.Club or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

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

🔗 CONNECT WITH DataTalksClub

Join the community - https://datatalks.club/slack.html

Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/...

Check other upcoming events - https://lu.ma/dtc-events

LinkedIn - / datatalks-club

Twitter - / datatalksclub

Website - https://datatalks.club/

  continue reading

184 episodes

Artwork
iconShare
 
Manage episode 471379213 series 2831626
Content provided by DataTalks.Club. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by DataTalks.Club or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

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

🔗 CONNECT WITH DataTalksClub

Join the community - https://datatalks.club/slack.html

Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/...

Check other upcoming events - https://lu.ma/dtc-events

LinkedIn - / datatalks-club

Twitter - / datatalksclub

Website - https://datatalks.club/

  continue reading

184 episodes

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