Senior Staff Software Engineer, Host Pricing & Settings

Airbnb

Senior technical contributor at Airbnb owning ML serving architecture with a focus on pricing strategies and model performance. Collaborating with cross-functional teams to ensure robust solutions.

Posted 7/1/2026full-timeRemote • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and implementing production ML systems, focusing on feature store design, model schema management, and ensuring consistency in online/offline inference. Proven leadership in driving cross-team technical initiatives and mentoring engineering teams through complex infrastructure challenges.

Highest-signal resume keywords

Backend EngineeringProduction ML SystemsJava ProgrammingFeature Store DesignHigh-Scale Data Pipelines

ATS Keywords

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Hard Skills

JavaKotlinScalaPythonML Systems DesignFeature EngineeringModel VersioningAPI DesignData ContractsMulti-Tenant Infrastructure

Soft Skills

MentoringCross-Team CollaborationTechnical Leadership

Tools & Technologies

SparkAirflowKafka

Industry Keywords

Data-Intensive InfrastructureOnline/Offline InferenceBatch ProcessingReal-Time Data PipelinesPoint-In-Time Correctness

Tech Stack

Tools & technologies

AirflowJavaKafkaKotlinPythonScalaSpark

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Disability inclusive application and interview process