Favorite Parts of Working in Tech at Meta as a Data Linguistic Analyst

I love all the technical stuff. That's why I chose this job, to get closer to that technical work. I take a lot of pride in being close to a technology that's going to impact so many people.

I also take that with a lot of responsibility because the amount of reach that AI is going to have, not just today but five to 10 years in the future, is going to be massive. So, I think being serious about that is very interesting work to be done.

There's a lot of conversations I have with people internally about that, that are fascinating. I love networking with people outside of work too, to talk about AI and my own personal take from a linguistic point of view. I'm not necessarily an engineer, but I lean more towards the philosophical side. I love talking about that stuff too.

Honestly, doing all the research is just my favorite thing. I love reading research papers, even if I don't understand them. I love the work that goes into toiling with those equations, or with the models, or with the phrasing of words. Someone else puts so much time, thought, and resources into developing whatever it was that they wrote a whole paper about.

Sometimes these things can be revolutionary. So, I've really enjoyed learning about all of the architectures, learning about things like retrieval-augmented generation, which I think is going to be the next big thing. So much work is being done within the research community to make things more open source or more accessible. They're also working to make the process a bit more transparent and ethical along the way.

It's really inspiring and gives me a lot of hope for the future. I think there are a lot of people that talk about AI in a doom-and-gloom sense, and that is pretty scary. There's something to that in terms of the whole science fiction thing, and there will always be people who warn about the worst-case scenarios.

But I think it's definitely needed to balance the worst-case scenario with the best-case scenario. We can really understand those better by looking really hard at what we're working with right now, what's changing so fast, and what's going to be accessible, practical, and economical.

I really, really enjoy thinking about all that stuff all day long, maybe too much. But it's really interesting. And I love talking to people about it too, so that's great.