Build career capital relevant for things like software engineering or machine learning engineering for AI safety.
Random, but a piece of advice that I’ve heard is that career capital for these things is only useful for getting your foot in the door (e.g. getting a coding test) and then your actually performance (rather than your resume) is what ends up getting you/not getting you the job. If you think you can succeed at this, I think it would almost certainly be better to just directly optimize for getting to a performance level that’s good enough for the AI safety job you want, rather than spending a few years software engineering (which might still be useful, but would be a less optimal way to spend your time, probably). I recommend reaching out to any AI safety orgs you hope to work at to confirm whether this is the case, in case you can get a few additional years of impact.
ETA: That said, ignoring personal fit, probably: AI safety paths where you skip the SWE ~= community building path >> software engineering at a start-up
Also, if you want to chat about Lightcone and/or Redwood, I’m doing work trials for both of their generalist roles (currently at Redwood, switching to Lightcone soon)--feel free to DM me for my Calendly :)
but a piece of advice that I’ve heard is that career capital for these things is only useful for getting your foot in the door (e.g. getting a coding test) and then your actually performance (rather than your resume) is what ends up getting you/not getting you the job.
In my experience, most orgs are much more excited about bringing on “senior engineers” than “junior engineers”, and often the only way to get the performance to be a “senior engineer” is to work in a company to build those skills. It doesn’t have to take long though.
your actually performance (rather than your resume) is what ends up getting you/not getting you the job.
There are many roles of engineer and I think for senior people in the interview process, experience, and “gravitas” or something helps.
I know someone who told their FAANG recruiter that they didn’t like LeetCode. The recruiter, who they didn’t know, then gave their personal number and texted out problems. Later, when the person didn’t pass, the recruiter then gave them a mulligan to do the test again. This person’s role was not an SWE, they were sort of meta to a “canonical” software engineer.
(Technically, the role was “Machine Learning Engineer” but this might give the wrong message because probably means something different at a FAANG versus Anthropic or Ought).
career capital for these things is only useful for getting your foot in the door (e.g. getting a coding test)
Career capital also determines what your “level” is, and there are huge differences between levels in compensation and productivity. An entry engineer versus a strong, generalist lead engineer (that can carry a team or a startup) is a hugely different role. It seems hard to gain this experience/ability from the outside.
If you think you can succeed at this, I think it would almost certainly be better to just directly optimize for getting to a performance level that’s good enough for the AI safety job you want,
rather than spending a few years software engineering (which might still be useful, but would be a less optimal way to spend your time, probably)
I think the two text blocks above might be basically saying the same thing, at least for the OP.
Someone I know spoke to Anthropic, and there is a strong demand for senior, strong engineering talent (e.g. systems design, carrying a whole project). This is the same talent that everyone wants.
I’m mostly writing content for onlookers. Please correct me if I’m wrong.
Random, but a piece of advice that I’ve heard is that career capital for these things is only useful for getting your foot in the door (e.g. getting a coding test) and then your actually performance (rather than your resume) is what ends up getting you/not getting you the job. If you think you can succeed at this, I think it would almost certainly be better to just directly optimize for getting to a performance level that’s good enough for the AI safety job you want, rather than spending a few years software engineering (which might still be useful, but would be a less optimal way to spend your time, probably). I recommend reaching out to any AI safety orgs you hope to work at to confirm whether this is the case, in case you can get a few additional years of impact.
ETA: That said, ignoring personal fit, probably: AI safety paths where you skip the SWE ~= community building path >> software engineering at a start-up
Also, if you want to chat about Lightcone and/or Redwood, I’m doing work trials for both of their generalist roles (currently at Redwood, switching to Lightcone soon)--feel free to DM me for my Calendly :)
In my experience, most orgs are much more excited about bringing on “senior engineers” than “junior engineers”, and often the only way to get the performance to be a “senior engineer” is to work in a company to build those skills. It doesn’t have to take long though.
There are many roles of engineer and I think for senior people in the interview process, experience, and “gravitas” or something helps.
I know someone who told their FAANG recruiter that they didn’t like LeetCode. The recruiter, who they didn’t know, then gave their personal number and texted out problems. Later, when the person didn’t pass, the recruiter then gave them a mulligan to do the test again. This person’s role was not an SWE, they were sort of meta to a “canonical” software engineer.
(Technically, the role was “Machine Learning Engineer” but this might give the wrong message because probably means something different at a FAANG versus Anthropic or Ought).
Career capital also determines what your “level” is, and there are huge differences between levels in compensation and productivity. An entry engineer versus a strong, generalist lead engineer (that can carry a team or a startup) is a hugely different role. It seems hard to gain this experience/ability from the outside.
I think the two text blocks above might be basically saying the same thing, at least for the OP.
Someone I know spoke to Anthropic, and there is a strong demand for senior, strong engineering talent (e.g. systems design, carrying a whole project). This is the same talent that everyone wants.
I’m mostly writing content for onlookers. Please correct me if I’m wrong.