Airbnb Senior Data Engineer ML Infrastructure 

United States 

48529149

The Difference You Will Make:

As part of our team, you'll build the essential AI/ML data foundations powering all AI/ML use cases across Airbnb—spanning Trust & Safety, Payments, Customer Support, Marketing, Search Ranking, and more. You’ll define and implement industry-leading best practices, pipelines, and tools to streamline data creation and consumption, ensuring efficiency, consistency, and compliance. Your contributions will significantly accelerate AI/ML innovation, enabling rapid development and deployment of high-quality, impactful AI/ML solutions company-wide. Additionally, you'll play a pivotal role in shaping our cutting-edge Generative AI infrastructure, positioning .

A Typical Day:

• Design, build, automate, and maintain robust, scalable data pipelines using SparkSQL, Scala, and Airflow.
• Develop and optimize data models ensuring high-quality, consistent, and accurate data to support broad AI/ML product feature decisions.
• Collaborate closely with peer ML Infra teams to deliver automated data solutions driving AI/ML acceleration.
• Contribute to scalable GenAI infrastructure by leveraging foundational language and vision models to create high quality datasets that power cutting edge GenAI applications.
• Partner with key customer teams to deliver high-impact, high-quality datasets core to Airbnb's roadmap.
• Utilize leading open-source technologies including Spark, Airflow, Ray, MLFlow, TensorFlow, PyTorch, Docker, Kubernetes, and more.

Your Expertise:

• 5+ years of relevant industry experience (BS/Masters) or 2+ years with a PhD.
• Strong coding skills in Python, Java, or equivalent languages.
• Hands-on experience with distributed processing technologies (Spark, Kafka, Flink, Hadoop) and distributed storage (HDFS, S3).
• Solid knowledge of data warehousing concepts and databases (e.g. PostgreSQL, MySQL, Redshift, BigQuery, ClickHouse).
• Expertise building scalable ETL pipelines using schedulers like Airflow, Luigi, Oozie, or AWS Glue.
• Proven ability to analyze large datasets, identify insights, and drive impactful product solutions.
• Excellent written and verbal communication skills; comfortable collaborating cross-functionally.
• Experience building end-to-end Machine Learning platforms and deploying ML models.
• Familiarity with Kubernetes, Docker, and modern infrastructure tools.
• Deep understanding of distributed systems and engineering best practices.

Offices: United States