Staff Machine Learning Engineer, Listings and Host Tools Data and AI

Airbnb Airbnb · Consumer · United States · Software Engineering

Staff Machine Learning Engineer at Airbnb to build and productionize ML models and pipelines for Listings and Host Tools, focusing on host personalization and experience. This role involves working with large-scale data, collaborating with cross-functional teams, and developing end-to-end ML infrastructure and serving APIs.

What you'd actually do

  1. Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases.
  2. Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact.
  3. Prototype machine learning use cases for use in the product, and work with stakeholders to iterate on requirements.
  4. Develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
  5. Design and build services, API to enable serving ML model driven data to product use cases.

Skills

Required

  • 8+ years of industry experience in applied Machine Learning
  • MS or PhD in relevant fields
  • Natural Language Processing
  • Computer Vision
  • Scala
  • Python
  • Java
  • C++
  • Tensorflow
  • PyTorch
  • Kubernetes
  • Spark
  • Airflow
  • Hive
  • Machine Learning best practices
  • gradient boosted trees
  • neural networks/deep learning
  • optimization
  • personalization
  • recommendation
  • anomaly detection
  • end-to-end Machine Learning infrastructure
  • productionizing Machine Learning models
  • integrating to product use cases
  • architectural patterns of a large, high-scale software applications
  • well-designed APIs
  • high volume data pipelines
  • efficient algorithms
  • test driven development
  • A/B testing
  • incremental delivery and deployment

What the JD emphasized

  • Must have experience in both Natural Language Processing and Computer Vision.
  • Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models, as well as integrating to product use cases.

Other signals

  • productionize ML models
  • build and operate ML pipelines
  • design and build serving APIs