Senior Staff Software Engineer, Host Pricing & Settings

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 Host Pricing & Settings team builds the platform and tools that help hosts run their business — with pricing strategies informed by market intelligence, comparable listings, and demand signals. We partner with Search, Listings, Tax, and Payments to ensure our guidance is accurate, timely, and trusted.

Behind every pricing recommendation is a sophisticated ML system undergoing a fundamental rearchitecture. Our north star: a serving infrastructure where training, inference, and evaluation are consistent by design — features from a centralized store, model composition in one place, and backfills available on demand so data scientists and MLEs can evaluate candidates in days, not weeks.

The Difference You Will Make:

As a senior technical individual contributor, you will own the technical strategy for the full Modeling → ML Serving → API interface across the Host Pricing org. Although you will be at one of our highest levels of seniority, all individual contributors at Airbnb are Software Engineers — you are expected to be hands-on and contribute code.

• 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.

A Typical Day:

• 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 revi