AI Safety Hiring Snapshot

Method and limits

How the data is collected and classified, how the rules were checked by hand, and what changed when the method was corrected.

The question

What share of the jobs AI safety organizations are advertising right now could someone early in their career realistically apply for? "Early in their career" means two years of relevant full-time experience or less: a strong new graduate, or someone moving over from another field.

Where the data comes from

Roles are read straight from each organization's own hiring system rather than from a curated job board, which avoids the selection built into those boards. Every organization included publishes a machine-readable feed through Greenhouse, Lever or Ashby, so the whole collection runs unattended each week. The 30 September 2026 snapshot holds 141 concrete vacancies.

Organizations with no feed are left out rather than read by hand. Hand capture was tried for four of them (GovAI, Apart Research, Redwood Research, Palisade Research) and dropped: the rows went stale between captures, and leaving those organizations out moves the headline share by less than one percentage point. Every collection is also compared with the one before for organizations that fall to zero, because a hiring feed that has been switched off looks exactly like an organization that stopped hiring. That check caught the Center for AI Safety's move from Lever to Greenhouse in July 2026.

Standing "expression of interest" and "talent community" listings are kept in the data but left out of every vacancy count.

Which organizations count

An organization is in if AI safety, security or governance is its main purpose and it has a hiring system we can read. That includes nonprofits, one government body (the UK AI Security Institute) and four safety-focused companies (Apollo Research, Goodfire, Haize Labs, Irregular). The companies sell products and hire sales and marketing staff accordingly, so the findings page shows every figure with and without them. Anthropic is tracked as a frontier-lab comparison and never mixed in. The coverage page lists every organization considered, including the ones left out and why.

How roles are classified

Three published rules, all in classify.py, with a regression test for each fix in test_classify.py:

A role reads as open if its title carries an entry marker, or (with no senior marker) its text states an open door or a floor of two years or less. It reads as needs more experience if the title is senior or the floor is above two years, and as doesn't say otherwise. Kind of work (research, engineering, operations and so on) comes from title keywords, with the hiring system's department as a fallback.

Checking the rules by hand

Rules miss things, so every one of the 141 vacancies in the 30 September 2026 snapshot was also read in full and labelled by hand, with the line that decided each label recorded next to it (download the labels). The labels mean:

The findings page reports these hand labels. The rules are what keep the weekly figures and the role list up to date between audits, so it matters how well they match:

Hand label ↓ · Rules →OpenDoesn't say Needs moreTotal
Open to early-career222125
Doesn't say117523
Needs more experience1256793

The rules agree with the hand labels on 106 of 141 vacancies. Of the 24 they call open, 22 are open by hand; of the 25 open by hand, they find 22. Two caveats. The open-door phrases were written after reading this snapshot, so this agreement is partly by construction, and the real test is the next audit. And the audit caught mistakes in both directions: one hand label was corrected after the rules found a requirement the first reading missed.

The rules' main weakness is on the other side. 25 roles they cannot place are, on reading, clearly closed: a required PhD, "several years" written in words, a leadership scope described rather than titled. So the rules overstate "doesn't say" and understate "needs more experience", while their count of open roles stays close. For comparison, titles alone flag 4% of vacancies as open, about four times fewer than the hand-checked 18%.

Where the rules and the hand labels disagree on "open"
OrganizationRoleHandRulesWhy
Apollo ResearchFinance ManagerDoesn't sayOpen to early-careermust-haves unstated; 2+ years only a nice-to-have
Eleos AIResearch ScientistNeeds more experienceOpen to early-careertrack record leading published ML research
GoodfireSales Development RepresentativeOpen to early-careerDoesn't sayno experience required; SDR background only preferred
KairosGeneralist (Groups)Open to early-careerDoesn't saya past university AI safety group organizer
LawZeroOperations Admin Lead – Executive OfficeOpen to early-careerNeeds more experience2 to 5 years of executive support experience

What to keep in mind

Corrections

This project publishes its mistakes. Every figure on the site is re-computed from the raw snapshots with the current rules, so older figures quoted elsewhere may differ.