Senior Compensation Partner, Technology

Airbnb · San Francisco, United Statessenior

En corto

▸Especialista en compensación para tecnología en Airbnb, con enfoque en ingeniería, IA/ML y ciencia de datos.
▸Diario: asesorías estratégicas, diseño de marcos de pago global, liderazgo en decisiones clave de reclutamiento y retención.
▸Destacado: liderazgo en marcos de benchmarking que combinan datos de encuestas con señales de reclutamiento en tiempo real.

Proficiency in English required for collaboration across global teams.

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¿Qué piden?

✓Experiencia comprobada en compensación en empresas tecnológicas de alto crecimiento.
✓Capacidad para liderar decisiones estratégicas con impacto en reclutamiento y retención de talento técnico.
✓Profundidad técnica para entender roles en ingeniería, IA/ML y ciencia de datos.
✓Habilidades avanzadas en análisis de datos y modelado para marcos de compensación.
✓Experiencia trabajando con líderes técnicos de alto nivel y equipos de talento.
✓Capacidad para construir herramientas y modelos que apoyen la toma de decisiones en compensación global.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

Total RewardsCompensation StrategyEquity AwardsMarket BenchmarkingRecruiting SignalsRole Evaluation FrameworksData AnalysisGlobal Pay ModelsAI/ML Talent StrategyStakeholder Advisory

¿A quién escribirle en Airbnb?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Total Rewards Compensation team serves as a strategic advisor to business leaders, managers, and employees across Airbnb. We are compensation experts with a deep understanding of our stakeholders, problem solvers who use data and insights to drive value, and partners who build the tools, models, and frameworks that support sound compensation decision-making across the company. This role sits within the Compensation function and will work closely with the Technology organization and cross-functional partners including Talent Directors, Recruiting, People Analytics, Finance, and Legal. The Difference You Will Make: We are looking for a Senior Compensation Partner to own Airbnb's compensation strategy for the Technology organization, covering functions such as Engineering, Infrastructure, ML/AI and Data Science. You will be the primary Total Rewards advisor to Technology leadership and the compensation point of contact for Talent Directors and Recruiting, defining how Airbnb competes for AI, ML, and frontier engineering talent. Working alongside our regional Total Rewards Partners, you will hold a global view of how we pay technical talent across all markets. Beyond your client group, you will contribute to the design and strategy of complex global programs, lead core Total Rewards priorities, and build the models and tools the broader Compensation team relies on. You are equally credible advising our most senior technical leaders and in the data behind the recommendation. A Typical Day: • Serve as the senior compensation advisor to Technology leadership across functions such as Engineering, Infrastructure, ML/AI, and Data Science, owning the organization's most consequential decisions: contested offers, retention actions, annual equity awards, and precedent-setting leveling exceptions • Provide direction and counsel to multiple Talent Directors and their teams, and carry recommendations to senior leadership and cross-functional executives across Talent, Finance, and Legal • Own Airbnb's market positioning for technical talent and the frameworks behind it: benchmarking methodology that supplements survey data with recruiting signals and real-time sources, role evaluation that weights AI expertise, research impact, and scarce skills, and su

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