
5001 - 10000 employees
Founded 2007
✈️ Travel
📦 Logistics
🛍️ eCommerce
💰 Post-IPO Equity on 2020-12
Travel • Logistics • eCommerce
Airbnb is a global online marketplace that connects people looking for accommodation with hosts offering unique and diverse lodging options, often in residential properties. Users can book spaces ranging from one-bedroom apartments to entire homes and boutique hotels. Airbnb also offers experiences, allowing guests to book activities hosted by locals, providing an authentic travel experience.
🕒 July 1
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5001 - 10000 employees
Founded 2007
✈️ Travel
📦 Logistics
🛍️ eCommerce
💰 Post-IPO Equity on 2020-12
Travel • Logistics • eCommerce
Airbnb is a global online marketplace that connects people looking for accommodation with hosts offering unique and diverse lodging options, often in residential properties. Users can book spaces ranging from one-bedroom apartments to entire homes and boutique hotels. Airbnb also offers experiences, allowing guests to book activities hosted by locals, providing an authentic travel experience.
• Define the architecture and contracts governing how models move from development to production — feature store design, model schema management, online/offline inference consistency, and multi-version support. • Lead the buildout of a unified serving stack that eliminates per-model one-off implementations and gives data scientists a turnkey path from training to production. • Architect backfill and evaluation infrastructure so the modeling team can simulate production inference over historical data in days, not weeks. • Establish domain contracts between Modeling and Serving so each team can move independently with clear, enforced interfaces. • Review and evolve the ML serving architecture — making tradeoff calls on feature pipeline design, model composition, and API interfaces. • Write and review code for feature engineering jobs, feature store configurations, and serving service endpoints. • Partner with Data Science, MLE, MLI and core Pricing & Availability systems BE teams to define artifact handoffs and integration contracts. • Drive milestone planning across the Host Pricing & Settings org, sequencing work to deliver value incrementally. • Mentor engineers through design reviews and hands-on pairing on the hardest infrastructure problems.
• 12+ years in backend or platform engineering, with substantial experience building production ML systems or data-intensive infrastructure. • Strong programming skills in Java, Kotlin, Scala, and/or Python. • Deep understanding of ML systems design: feature stores, training/serving consistency, model versioning, and online/offline inference pipelines. • Experience with high-scale batch and real-time data pipelines (Spark, Airflow, Kafka, or equivalent), including point-in-time correctness for backfills. • Expertise with architectural patterns of large, high-scale applications — well-designed APIs, efficient data contracts, multi-tenant serving infrastructure. • Proven ability to lead cross-team technical initiatives spanning ML and platform engineering.
• Disability inclusive application and interview process
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