JobHabor

Senior Staff Software Engineer

Airbnb

Location
US - Remote Eligible
Workplace
Remote
Employment
Full Time
Salary
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Posted 2mo ago

The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.

Responsibilities

  • Define architecture and contracts for ML model deployment
  • Lead buildout of a unified serving stack
  • Architect backfill and evaluation infrastructure
  • Establish domain contracts between Modeling and Serving
  • Review and evolve ML serving architecture
  • Write and review code for feature engineering and serving endpoints
  • Partner with Data Science, MLE, MLI and core Pricing & Availability teams
  • Drive milestone planning and incremental value delivery
  • Mentor engineers through design reviews and pairing

Requirements

  • 12+ years in backend or platform engineering
  • 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, online/offline inference pipelines
  • Experience with high-scale batch and real-time data pipelines (Spark, Airflow, Kafka, or equivalent)
  • Experience with point-in-time correctness for backfills
  • Expertise with architectural patterns of large, high-scale applications
  • Experience with well-designed APIs, efficient data contracts, multi-tenant serving infrastructure
  • Proven ability to lead cross-team technical initiatives spanning ML and platform engineering

Preferred

  • Production experience with Chronon, Tecton, Feast, or equivalent
  • Experience with online/offline consistency and backfill automation
  • Experience with model schema management, multi-version support, and model composition frameworks
  • Track record defining and enforcing technical contracts between ML modeling, MLI, serving teams and/or product surfaces
  • Measurable impact improving the speed at which ML teams evaluate candidate models and ship to production

Skills

  • Java
  • Kotlin
  • Scala
  • Python
  • Spark
  • Airflow
  • Kafka
  • Chronon
  • Tecton
  • Feast

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