Listen Labs

AI-led user interview platform
Last updated:
February 4, 2026
Company details
HQ
HEADCOUNT
25-99
ORG TYPE
Startup
SECTOR
Technology & Digital
About the company
Listen Labs sells an AI-led user research product that runs interviews and delivers insights faster than traditional research cycles. The company positions the product as “autonomous market research”, covering study design, participant sourcing, interviews, and analysis. Public materials emphasise speed to insight and replacing manual research operations with an AI workflow. Recent founder posts and media coverage frame Listen Labs as a fast-scaling startup after a large funding raise.
Locations and presence
Listen Labs hires heavily in San Francisco, with multiple roles listed as on-site. Public reporting also describes expansion plans into additional cities including New York, London, and Stockholm.
Palpable Score
49.3
/ 100
Listen Labs looks like a high-growth startup hiring across go-to-market and customer functions, but the visible roles skew experienced rather than truly entry-level. The company’s public hiring materials provide limited detail on interview stages, junior coaching, and early-career progression, which caps the score.
Pillar 1: Early-career access

Score

9.0
/ 20
  • The company’s live job board is dominated by experienced GTM roles (for example Account Executive and Customer Success Manager), which restricts access for new grads.
  • Listen Labs lists a Business Development Representative role, which is often an early-career entry point, but the overall mix still leans senior.
  • The company does not publicly show internships, apprenticeships, or “0–1 year” roles on the main hiring pages, limiting first-job pathways.

Pillar 2: Hiring fairness and transparency

Score

12.3
/ 20
  • The company uses a structured ATS-style job board (Ashby) with clearly separated teams, locations, and employment type, which helps candidates understand what they are applying to.
  • Listen Labs job pages are light on interview process detail, such as number of stages, take-home tasks, or decision timelines, which reduces predictability for early-career applicants.
  • The company does not consistently publish salary ranges on the public listings surfaced from the main careers flow, which makes it harder to assess fairness upfront.

Pillar 3: Learning and support

Score

10.7
/ 20
  • The company’s product domain implies strong learning-by-doing opportunities for junior hires (customer conversations, study design constraints, and measurable outcomes), but those supports are not described as coached training.
  • Listen Labs does not publicly outline onboarding, ramp plans, or manager 1:1 expectations in the roles visible on the hiring pages.
  • The company’s roles are largely “own the number” GTM positions, which can be valuable development, but public materials do not specify mentoring, shadowing, or structured enablement for early-career staff.

Pillar 4: Pay fairness and stability

Score

11.0
/ 20
  • The company posts full-time roles with clear location and team ownership, which is a baseline stability signal for early-career candidates.
  • Listen Labs does not consistently publish compensation ranges on the core public job listings, which caps pay fairness scoring due to missing evidence.
  • The company’s public careers pages do not provide a detailed benefits breakdown (health, pension, parental leave, PTO specifics) that early-career candidates can compare across offers.

Pillar 5: Early-career outcomes

Score

6.3
/ 20
  • The company is early in its scale-up phase, so there is limited public time-series evidence of junior promotion cycles or 12–24 month retention outcomes.
  • Listen Labs has strong growth narratives in public announcements, but those do not translate into observable early-career progression data such as internal mobility examples or conversion pathways.
  • The company’s LinkedIn footprint supports that Listen Labs is hiring and growing, but public profiles do not provide enough aggregated early-career progression patterns to score outcomes higher.

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