This is the advice I wish I had when I started trying to become an AI safety research engineer.

The Landscape

Start by working out which issues you care about. If you don't care about any, hiring managers don't care how good of an engineer you are. You shouldn’t blindly agree with all issues in AI safety. Predicting the future is hard, so many of us will be wrong.

Because everyone is so focused on the shared AI safety mission, people are willing to help you. When entering the field, people will work with you to upskill.

Hence, it's worth being proactive. Email researchers about their papers. But don’t take it personally when someone is too busy to respond. The AI Safety Map gives a good visual overview of who's doing what. Going to conferences and AI safety coworking spaces is particularly important. The field is small, so people who write important papers are often at conferences.

AI safety isn't like medicine. There is no clear path you can slot into and expect to come out with a job. Jobs exist, but you're more likely to find them through people than job boards. Go talk directly to people who have problems they want to solve.

Expect upskilling and job hunting to take about a year. It depends on your background, but it's not going to be quick. Make sure you can afford the career transition.

Remote work is common in AI safety. However, being in a hub means you'll learn a lot more. Actually going to San Francisco or London is really good. I work from Christchurch, but I regularly travel to meet people and learn.

Skills You Need

The skills you need depend on the problems you want to solve, so figure that out first. To start, get a good lay of the land on different research agendas. A good place to start is the Bluedot Technical Alignment course. You can also read stuff on the Alignment Forum to get a range of perspectives.

Technical Skills

Python is king. Language models are written in Python. You just have to learn it. Once you've got that down, picking up other languages is helpful.

You also want to get good at deep learning using PyTorch. It's hard to do technical work without understanding how deep learning works.

AI safety focuses on language models, so Andrej Karpathy's "Replicating GPT-2 from scratch" is an excellent resource for understanding how those work. If you want to go even deeper, the ARENA curriculum is great. In my eyes, it's the gold standard for bei...

Zachary Gunderson

Zachary Gunderson