Senior Staff Software Engineer (ML Infrastructure)

TL;DR

Senior Staff Software Engineer (ML Infrastructure): Architecting and building a unified ML serving platform for host pricing systems with an accent on feature store design, model inference consistency, and high-scale data pipelines. Focus on defining technical strategy for the full modeling-to-serving lifecycle and enabling data scientists to evaluate and deploy models with high velocity.

Location: Must be based in the United States in a state where Airbnb, Inc. has a registered entity. Role is remote-eligible with occasional office/offsite attendance.

Company

Airbnb is a global platform connecting hosts and guests through unique stays and experiences, operating at a massive scale.

What you will do

• Own the technical strategy for the full modeling, ML serving, and API interface across the Host Pricing organization.
• Architect a unified serving stack to eliminate per-model implementations and streamline the path from training to production.
• Design and implement feature store solutions, model schema management, and online/offline inference consistency.
• Build backfill and evaluation infrastructure to enable rapid simulation of production inference over historical data.
• Define domain contracts between modeling and serving teams to ensure independent development and system reliability.
• Mentor engineers through design reviews and hands-on pairing on complex infrastructure challenges.

Requirements

• 12+ years of experience in backend or platform engineering with a focus on production ML systems.
• Strong programming proficiency in Java, Kotlin, Scala, or Python.
• Deep expertise in ML systems design, including feature stores, model versioning, and inference pipelines.
• Experience with high-scale data processing tools like Spark, Airflow, or Kafka.
• Proven ability to lead cross-team technical initiatives and define architectural patterns for large-scale applications.
• Must be a resident of a US state where Airbnb has a registered entity.

Nice to have

• Production experience with feature store technologies like Chronon, Tecton, or Feast.
• Experience with model composition frameworks and multi-version support.
• Track record of defining technical contracts between ML modeling and serving teams.

Culture & Benefits

• Commitment to inclusion and belonging with a focus on diverse talent.
• Opportunity to work on high-scale infrastructure impacting millions of hosts.
• Collaborative environment with a focus on technical excellence and mentorship.
• Support for disability-inclusive application and interview processes.