careerladder.fyi › Career paths › World Labs
How people got jobs at World Labs
What 60 people did before they joined World Labs: where they worked, what they studied, which role they came in through, and how long it took.
60
people in our data got there
74%
had a graduate degree first (of those listing one)
8
typical years since first job
- The most common step right before: from other companies (75%).
- The most common way in was Member of technical staff (23% joined in that kind of role).
- Of those who list their education, 74% had a graduate degree before arriving and 33% a PhD.
- The typical person arrived about 8 years after their first job.
- The most common earlier employer: Meta (15% had worked there).
How World Labs compares
- 33% had a PhD, above the 19% across other frontier AI labs, the 2nd-highest of the 19 in our data.
- 74% had a graduate degree, above the 66% across other frontier AI labs.
- People arrived about 5 years earlier in their careers than at the typical one of the other frontier AI labs (8 vs 13 years since their first job).
Among people who list their education; places with at least 10 such people.
Show as a table
| People listing education | Share | |
|---|---|---|
| Google DeepMind | 58 | 41% |
| World Labs (this page) | 39 | 33% |
| Physical Intelligence | 31 | 32% |
| Sakana AI | 41 | 29% |
| Cohere | 40 | 28% |
| Hugging Face | 34 | 24% |
| Stability AI | 40 | 22% |
| SpaceXAI | 17 | 18% |
| Thinking Machines Lab | 29 | 17% |
| OpenAI | 41 | 17% |
| Anthropic | 28 | 14% |
| Black Forest Labs | 32 | 12% |
| EleutherAI | 26 | 12% |
| Reflection | 20 | 10% |
| Mistral AI | 36 | 8% |
| Skild AI | 39 | 8% |
| Poolside | 31 | 6% |
| Cognition | 27 | 4% |
| Perplexity | 24 | <1% |
Show as a table
| Median years | ||
|---|---|---|
| SpaceXAI | 18 yrs | |
| Anthropic | 15 yrs | |
| Mistral AI | 15 yrs | |
| OpenAI | 14 yrs | |
| Perplexity | 14 yrs | |
| Reflection | 14 yrs | |
| Thinking Machines Lab | 14 yrs | |
| Stability AI | 14 yrs | |
| Poolside | 13 yrs | |
| Cognition | 13 yrs | |
| Cohere | 13 yrs | |
| Black Forest Labs | 10 yrs | |
| Physical Intelligence | 10 yrs | |
| Google DeepMind | 10 yrs | |
| Sakana AI | 9 yrs | |
| Skild AI | 9 yrs | |
| World Labs (this page) | 8 yrs | |
| Hugging Face | 8 yrs | |
| EleutherAI | 5 yrs |
Which role they joined in
Kinds of role with fewer than 5 people are combined into "All other roles".
Show as a table
| People | Share | |
|---|---|---|
| Member of technical staff | 14 | 23% |
| Business & operations | 8 | 13% |
| Software engineering | 8 | 13% |
| All other roles | 25 | 42% |
| Founder general mgmt | 5 | 8% |
Show as a table
| People | Share | |
|---|---|---|
| Member of Technical Staff | 11 | 18% |
What they did right before
Show as a table
| People | Share | |
|---|---|---|
| From other companies | 45 | 75% |
| From Big Tech | 12 | 20% |
| Other | 3 | 5% |
Where they worked before
A person can count under more than one employer.
Show as a table
| People | Share | |
|---|---|---|
| Meta | 9 | 15% |
| 7 | 12% |
Education
Among the 39 of 60 people who list their education.
Show as a table
| People | Share | |
|---|---|---|
| Bachelor's | 10 | 26% |
| Master's | 13 | 33% |
| MBA | 3 | 8% |
| PhD | 13 | 33% |
How much experience they had
Among the 60 of 60 people with an earlier job listed.
Show as a table
| People | Share | |
|---|---|---|
| Under 1 year | 3 | 5% |
| 1-3 years | 5 | 8% |
| 3-5 years | 5 | 8% |
| 5-8 years | 15 | 25% |
| 8-12 years | 14 | 23% |
| 12+ years | 18 | 30% |
Where would your path lead?
Paste your LinkedIn or resume and see the ladders people like you climbed to World Labs, and how each step changes your chances.
Plan my path to World Labs →
Paste your LinkedIn or resume and see the ladders people like you climbed to World Labs, and how each step changes your chances.
Plan my path to World Labs →
Related
How these numbers are made. From 3k+ public career histories collected for careerladder.fyi (dated jobs, degrees and publications). The collection was built around particular employers, so people who reached well-known tech, AI and finance employers are over-represented: read shares as "among people in this dataset", not as hiring odds. Names are shown only when at least 5 people are behind them; smaller groups are combined into "Other". No individual profile is shown. Updated November 2026.