oceanparkway

I'm a 4-year SWE and considering transitioning into ML/AI, either through a lateral move into a relevant team or pursuing further education like a specialized course or degree.

I'm curious about others who have successfully shifted their focus to ML/AI. I'm thinking broadly -- supporting SWE at ML-focused company, MLops, research -- I know that's broad but given I'm considering my future without a clear plan, a broad perspective is helpful to me.

- What sparked your interest?

- How did you get started?

- Did you make an internal transition within your company, or switch jobs?

- What's your educational background and were there any gaps you sought to close to facilitate this transition?

- What challenges did you face, and what worked well?

Asking because I'd like the make the jump myself and thought I'd first solicit ideas re: deployment/management from folks who have completed the journey.

Motivating factors are $, read replicas, and having a log drain to datadog.

My wish list for making the transition myself is:

- Hetzner or similarly cheap

- DB on volume

- Read replicas for batch jobs (don't need load balancing b/w them and master db)

- Backup

- Datadog agent

- Easy upgrade pathway -> some kind of IaC deploy of new Supabase version