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Senior Machine Learning Engineer, Trust Foundational Modeling



Software Engineering
United States · Remote
Posted on Thursday, June 6, 2024

Airbnb was born in 2007 when two Hosts welcomed three guests to their San Francisco home, and has since grown to over 4 million Hosts who have welcomed more than 1 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.

The Community You Will Join:

Everyone at Airbnb thinks about trust, but our team obsesses over it daily. At the core of trust is safety, and thus we spend a significant amount of our time and energy keeping the community safe. The Trust team is responsible for protecting our community and platform from fraud while also ensuring our hosts, guests, homes, and experiences meet our high standards. We constantly work to fight against online fraud (such as monetary loss, compromised accounts, spam and scam in messages, fake inventory, etc.) as well as offline fraud (theft, property damage, personal safety, etc.). We also work on onboarding and screening of users, and think about complex topics like identity and reputation to ensure that every interaction with Airbnb helps build trust in us and our community. Trust Engineering is responsible for the technology vision and development of a complex stack that runs on every key interaction on the platform.

The Difference You Will Make:

As a technical individual contributor, you will partner closely with our collaborators across the broader technical organization. All individual contributors at Airbnb are Software Engineers which means we expect you to be hands on and contribute code.

A Typical Day:

As a machine learning engineer in Trust, your contributions will span a variety of shapes:

  • Work with large-scale structured and unstructured data to build and continuously improve cutting-edge machine learning models for Airbnb’s product, business, and operational use cases. Some recent works include:
    • Supervised model ensembles that include multiple DNNs and graph-based models
    • Contextual Decision engine
    • Unsupervised clustering models for natural language understanding
    • LLM experimentation with label taxonomy and manual agent automation
    • Optimizing ranking algorithms for search
  • Collaborate with a wide variety of business functions to predict and prevent physical safety and property damage incidents.
  • Develop new holistic machine learning model detection strategies by partnering with other teams across the Trust Organization.
  • Work collaboratively with cross-functional partners, including software engineers, data scientists, product managers, and operations to identify opportunities for business impact, and 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.
  • Enhance and extend risk investigation tools to enable efficient decision-making on behaviors that could result in physical safety or property damage incidents.
  • Create products to deter bad actors and restrict their usage on the platform.
  • Provide and educate on guest and host safety standards to mitigate vulnerabilities.

Your Expertise:

  • 5+ years of industry experience in applied machine learning or a MS or PhD in CS/ML fields.
  • Strong programming skills in Scala, Python, Java, C++, or equivalent languages, and data engineering skills.
  • Strong understanding of machine learning best practices (e.g., training/serving skew minimization, A/B testing, feature engineering, feature/model selection), algorithms (e.g., neural networks/deep learning, gradient boosted trees, optimization), and domains (e.g., natural language processing, computer vision, personalization and recommendation, anomaly detection).
  • Experience with any of these technologies: TensorFlow, PyTorch, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouses (e.g., Hive).
  • Experience building end-to-end machine learning infrastructure and/or building and productionizing machine learning models.
  • Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).
  • Experience with test-driven development, familiarity with A/B testing, incremental delivery, and deployment.
  • Experience with the Trust and Risk domain is a plus

Your Location:

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process.

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range
$185,000$223,000 USD