Senior Machine Learning Engineer, Trust

The Community You Will Join:

• Trust is essential to the success of the Airbnb platform for both guests and hosts. The Safety team invests significant effort in keeping the community safe and building this trust.
  
• We are responsible for detecting reservations with party intent that could violate Airbnb platform policies. Our goal is to block these users before check-in to prevent critical life safety incidents for our guests and hosts.
   

The Difference You Will Make:

• Guests provide signals about potential party intent during the booking process. Combining these signals with internally available data offers a significant opportunity to develop various heuristics and machine learning models to predict the likelihood of unauthorized parties.
• As a Senior Machine Learning Engineer on the Trust & Safety team, you will collaborate with product managers, data scientists, designers, and customer service operations to innovate new ways to predict and prevent critical life safety and property damage incidents on the platform.
• The problems you tackle will often be vague and ambiguous, requiring you to possess a strong curiosity to deeply investigate various user patterns and behaviors to understand how and where these life safety incidents might occur.

A Typical Day: 

• 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.
• Working together with a wide variety of business functions to stop critical life safety and property damage incidents in real time.
• Creating new holistic machine learning model detection strategies by collaborating with other trust and safety prevention teams around the Trust Organization.
• 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 fraud detection and mitigation.
• Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.

Your Expertise:

• 5+ years of industry experience in applied Machine Learning, inclusive MS or  PhD in relevant fields
• A Bachelor’s, Master’s or PhD in CS/ML or related field
• Strong programming (Scala / Python / Java/ C++ or equivalent) and data engineering skills
• Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization) and domains (eg. natural language processing, computer vision, personalization and recommendation, anomaly detection)
• 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, hig