“It depends”: what’s your prior experience, what kind of roles interest you, how big is the gap between what you have + a little ML knowledge/side projects?
I’d argue there’s a big need for people with solid fundamental CS, sysadmin, infra skills who can bridge the gap into ML practitioner/researcher understanding. Applications or inference generally are probably easiest to break into, especially if you already have service knowledge. If you want to work on distributed training or kernel/model optimization, you probably need to prove your chops there.
Neoclouds, startups in the AI space, maybe hw vendors are probably good places to look.
I’d argue there’s a big need for people with solid fundamental CS, sysadmin, infra skills who can bridge the gap into ML practitioner/researcher understanding. Applications or inference generally are probably easiest to break into, especially if you already have service knowledge. If you want to work on distributed training or kernel/model optimization, you probably need to prove your chops there.
Neoclouds, startups in the AI space, maybe hw vendors are probably good places to look.