Machine Learning Engineer, Community Support Engineering

About the Role

<div class="content-intro"><p><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.</span></p></div><p><strong>Your Location:</strong></p> <p><strong>This position is CHINA BASED</strong>. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. Your recruiter will inform you what cities you are able to work from depending on your personal legal working identity and Airbnb internal policies.</p> <p>&nbsp;</p> <p><strong>The Community You Will Join:</strong></p> <p>Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb.&nbsp;</p> <p>The Community Support Products (CSP) Machine Learning team is the core team responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances various AI models, ML services and tools including LLM fine-tuning and optimization, RAG/Search,&nbsp; LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb.&nbsp;</p> <p>The richness of Airbnb's data, the complexity of its marketplace and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to investing in long&nbsp;term innovation to solve the complex problems we face, and to do that we nee

Key Responsibilities

• 1

  Develop and deploy ML models solving real-world product and business problems.

• 2

  Conduct exploratory data analysis and feature engineering on large datasets.

• 3

  Evaluate models using rigorous metrics, iterate based on offline and online experiments.

• 4

  Collaborate with product and engineering teams to integrate ML into production.

• 5

  Publish and present research findings internally and externally.

• 6

  Monitor model performance and retrain as data distributions shift.

Requirements

• Bachelor's/Master's/PhD in Statistics, Math, CS, or related field.
• Strong Python and ML library proficiency (scikit-learn, TensorFlow, PyTorch).
• Experience with large-scale data processing (Spark, BigQuery).
• Solid understanding of statistical modelling and A/B experimentation.
• Excellent communication skills with both technical and non-technical audiences.

Skills Required

How The Selection Process Works

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