What archetypes does AIML Eng follow?
Curious to hear about what archetypes you think AI teams follow.
For ex: I think Specialist, Tech Leads are pretty common for AI teams. But we probably have a few archetypes like fixer that are slightly different in the skillset (dig through data, analyze common usecases).
Did meta have any additional archetypes for AI eng types?
Discussion
(3 comments)- 0
2 months agoTech Lead @ Robinhood, Meta, Course HeroI don't think Meta had any additional archetypes for AI/ML engineers as it didn't really have domain-specific archetypes in general. The wiki essentially had all the archetypes together in 1 doc even though some aren't applicable for certain fields. For example, product-hybrid was only really applicable for product engineers, particularly those on front-end. It wasn't on a separate "Staff Archetypes For Front-End Engineers" page or something.
For AI/ML, I mostly saw specialist and tech lead as well back at Meta, echoing your experience. AI/ML is a cutting-edge specialization, so it makes sense that there's a lot of specialist Staff+ engineers there.
The most senior MLE I saw specialized in computer vision and was E7 (Senior Staff). They had extremely deep computer vision knowledge (specialist) but also coded insanely fast (code machine). I think the code machine angle is what pushed them from E6 -> E7.
- 02 months agoTech Lead/Manager at Meta, Pinterest, Kosei
Given how large AI is, there is room for many archetypes even within AI.
- A lot of the work is infra-related, where Specialist or Code Machine is valuable.
- Some work is product-facing, where Tech Lead or Generalist is valuable
I talk about the different archetypes here in the Senior to Staff course.
- 22 months agoSenior Software Engineer [OP]LinkedIn
Great course! I went through the material and it resonated well.
Agree with this assessment. I think generally for business impact the lines do start blurring and you can't stick to your limited modeling work. You do need to own the E2E outcome.
