Airbnb Staff Machine Learning Engineer Support Products 

United States 

57502429

The Community You Will Join:

Some example projects we have shipped:

• Agent tools to investigate claims and possible fraud through real-time image, text, and user similarity search.
• Automated property damage claim item entity extraction.
• Advanced analytical data pipelines for monitoring performance, stability, and tool usage.
• An advanced ticket routing system to match user issues against available agent skills.
  

A Typical Day:

Your contributions take a variety of shapes:

• Work with large scale structured and unstructured multimodal data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases.
• Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
• 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.

Your Expertise:

• 9+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields.
• Strong programming (e.g. Python / Java / Kotlin) and data engineering skills.
• Depth of experience in Computer Vision or Natural Language Processing.
• Understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection).
• Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive).
• Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.
• Exposure to architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).
• Experience with test driven development, familiar with A/B testing, incremental delivery and deployment.