Senior Machine Learning Engineer - Marketing Technology

Airbnb, San Francisco OR Seattle

Who wouldn't want to work here?

Airbnb is a mission-driven company dedicated to helping create a world where anyone can belong anywhere. It takes a unified team committed to our core values to achieve this goal. Airbnb's various functions embody the company's innovative spirit and our fast-moving team is committed to leading as a 21st century company.

The Marketing Technology is a platform team with the goal of delivering best-in-class marketing automation tools and systems that are used by our stakeholders in Marketing (Brand and Performance), the Guest Experience and Hosting product development teams, Policy, and more.  Our Mission is to enable marketing and product teams to deliver highly personalized and relevant content to the Airbnb community, both on-site and off-site.


The Marketing Technology team spans five pillars: (1) Demand side platform (DSP) that powers programmatic advertising - both search and display, (2) Email marketing platform, (3) Landing page platform, (4) Communications and delivery infrastructure that enables promotional and transactional content delivery at scale across multiple offline channels (e.g. email, push, sms), (5) Machine learning and data pipelines that enable optimizations and personalization.


About The Role


We are looking for a ML Engineer to join the Marketing Technology ML team. In this role, you’ll have the opportunity to build a portfolio of reusable and scalable ML models that enable Airbnb to reach the right customer at the right time using the right channel with the right content. 

This will be done through collaborating with various teams in Airbnb including search infra, search relevance, teams within Marketing Technology to build and improve personalization for content, send time, targeting and a solid ML foundation.


  • Work with large scale user behavioral data to build ML products, examples include but not limited to :
    • Targeting models that help identify key user segments that can be used to optimize engagement with a user (ex. booking intent, user engagement rate predictions)
    • Content optimization models that identify right content to showcase to the user (ex. Personalize and Rank content sections in an email/ landing page)
    • Support omni-channel engagement by identifying the right channel and right time to engage with users. 
  • Collaborate closely with PM and Data Scientists to identify opportunities for business impact, leverage data to quantify outcome and participate in planning ML strategy and roadmap for the team.
  • Work closely with product and infra engineers to understand, refine, and prioritize requirements for shared machine learning models
  • Leverage third-party ML tools and in-house models & infrastructure, or build new ML systematic solutions tailored to Airbnb problems
  • Hands on development, productionize and operate ML models and pipelines at scale, including both batch and real-time use cases
  • Improve quality of existing ML models and infrastructure.
  • Develop scalable, reliable distributed systems.
  • Lead projects and mentor junior engineers 


Additional Qualifications

  • 8+ years of industry experience or a PhD + 6 years relevant industry experience
  • Experience developing machine learning models at scale from inception to impact
  • Strong coding skills in Python/Java/Scala or equivalent
  • Experience with C++, Spark a plus
  • Solid understanding of engineering best practices and complexities of models in production
  • 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.
  • Bonus: Experience building platforms, specifically marketing tools/technology, campaign management, ad tech

About Airbnb

Founded in August of 2008 and based in San Francisco, California, Airbnb is a trusted community marketplace for people to list, discover, and book unique accommodations around the world — online or from a mobile phone. Whether an apartment for a night, a castle for a week, or a villa for a month, Airbnb connects people to unique travel experiences, at any price point, in more than 33,000 cities and 192 countries. 

Want to learn more about Airbnb? Visit Airbnb's website.