Duolingo
Talent Attraction Partner
Pittsburgh, PA
Sponsorship not specified$119k-$161kDetected 1 day ago
CRMOutbound SalesProblem SolvingTime ManagementOrganizational Skills
> stay_score
odds of building a lasting career here
57Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →> community_outcomes
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About the role
- At Duolingo, you'll join a team that cares about educating our users, experimenting with big ideas, making fact-based decisions, and finding innovative solutions to complex problems.
- You'll have limitless learning opportunities and daily collaborations with world-class minds - while doing work that's both meaningful and fun.
Skills
- The offered salary is dependent upon several factors, including work experience, skills, and internal peer comparisons.
Compensation
- $119,000 - $161,000 USD
Benefits
- Take a peek at how we care for our employees' holistic well-being with our benefits here.
Equal opportunity
- Duolingo is proud to be an Equal Employment Opportunity employer.
- We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
- Fraud Warning: Unfortunately, there is a rise in scammers pretending to be real Duolingo employees.
- Duolingo and our employees will never ask for your Social Security number, bank details, or passport info, and we'll never ask you to deposit a check, purchase equipment, or exchange money during the interview process.
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This listing is sourced directly from Duolingo's careers page and normalized into a canonical job model.