Company details

San Francisco, CA

HEADCOUNT

25-99

ORG TYPE

Startup

SECTOR

Technology & Digital

WEBSITE

https://www.worldlabs.ai

About the company

World Labs is an AI research and product company focused on “spatial intelligence” and large world models that work with 3D environments. World Labs launched Marble, a product that generates spatially consistent 3D worlds from inputs like text, images, and video, with options to edit and export outputs for use in creative and technical workflows. World Labs has positioned Marble for use cases such as gaming, VFX, simulation, and robotics-related work. World Labs was co-founded by Fei-Fei Li and raised $230 million in early funding.

Locations and presence

World Labs lists San Francisco as the location for current open roles, and company policies publish a San Francisco mailing address. World Labs does not state remote or hybrid expectations on the public job posts reviewed, so working-location requirements are not verifiable from listings alone.

Palpable Score

39.5

/ 100

World Labs is not an early-career-focused employer right now because the public job board shows only two open roles and both are explicitly experienced hires. World Labs earns credit for unusually clear pay transparency and salary history protections, but the lack of junior entry points and limited public information about hiring process, onboarding, and outcomes keep the score low.

Pillar 1: Early-career access

Score

4.3

/ 20

The company shows only “Research Scientist – Generative Modeling” and “Senior Product Engineer” as open roles on the public careers board.

World Labs sets explicit experience bars on both roles, including “3+ years” for the Research Scientist posting and “6+ years” for the Senior Product Engineer posting.

The company does not list internships, new graduate roles, apprenticeships, or roles that mention “0–2 years” on the public job board reviewed.

‍

Pillar 2: Hiring fairness and transparency

Score

9.3

/ 20

The company publishes Equal Employment Opportunity language and offers reasonable accommodations via a dedicated hiring contact email on job posts.

World Labs discloses a California pay range and states the company does not request or consider salary history in making offers.

The company does not describe interview stages, assessment types, or timelines on the public listings reviewed, so candidates cannot verify what the process looks like before applying.

‍

Pillar 3: Learning and support

Score

6.3

/ 20

The company includes mentoring expectations in the Research Scientist job description, but the role is aimed at experienced hires rather than structured early-career development.

World Labs frames the working style as high-ambiguity and high-ownership in job posts, but the company does not describe onboarding, buddy systems, or manager training in public materials reviewed.

The company does not publish a learning budget, training program, or early-career support page that a new starter could rely on when choosing between offers.

‍

Pillar 4: Pay fairness and stability

Score

14.3

/ 20

The company publishes a base salary range of $250,000–$325,000 for both open roles in San Francisco, which is unusually transparent for a startup.

World Labs states total compensation includes base salary plus equity awards and an annual performance bonus on the job posts reviewed.

The company has no public pay information for early-career roles because no early-career roles were visible, so pay fairness for graduates cannot be assessed directly.

‍

Pillar 5: Early-career outcomes

Score

5.3

/ 20

The company does not publish early-career outcomes such as internship conversion rates, promotion timelines, or retention metrics.

World Labs has high-profile funding and product-launch coverage, but those sources do not provide verified information about internal progression for early-career hires.

The company does not have a clearly attributable, widely used public employee review footprint under the same name that matches the current San Francisco AI startup, which limits visibility into team-level experiences and churn risk.

‍