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.
Trust Engineering at Airbnb:
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 Org 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 and offline fraud. We also work on onboarding and screening of users, and think about complex topics such as identity to ensure that every interaction with Airbnb helps build trust in us and our community. Trust Engineering within Trust Org is responsible for the technology vision and development of a complex stack that runs on every key interaction on the platform.
We are looking for talented and self-driven Machine Learning Engineers (multiple openings, multiple levels) to join our Trust engineering teams to help build holistic and proactive defenses leveraging sophisticated Machine learning and other relevant algorithms. You will be working on highly impactful projects that are essential to stop bad actors from doing bad things on Airbnb.
What does being a Trust Machine Learning Engineer look like:
As a Trust Machine Learning engineer, you help keep Airbnb users safe by working across diverse teams and systems to enable sophisticated safety strategies. You are eager to understand complex systems top to bottom and thrive working across technologies and codebases. Your contributions take a variety of shapes:
- Design, build, productionize, operate and improve best-in-class Machine Learning solutions that keep Airbnb community safe. Example projects include: account takeovers, fake content, fake accounts, message spam.
- Build cutting edge Machine Learning models that are used as building blocks to create intelligent solutions that detect risks on Airbnb platform or help humans make decisions. Example modeling techniques include: natural language processing, computer vision, anomaly detection, clustering, embeddings.
- Develop reusable, highly differentiating and high-performing Machine Learning systems that enable fast model development, low-latency serving and ease of model quality upkeep. Example projects include: feature platform, model interpretability, hyperparameter optimization, concept drift detection.
- Work collaboratively with cross functional partners including software engineers, product managers, operations and data scientists to identify opportunities for business impact and to drive engineering decisions.
Who are we looking for:
- 5+ years (or PhD in relevant fields with 2+ years) industry experience in applied Machine Learning
- Strong coding skills in Scala / Python / Java or equivalent
- Deep understanding of Machine Learning best practices (such as training/serving skew minimization and A/B test) and algorithms (such as gradient boosted trees and DNNs)
- Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive)
- Experience or desire to work collaboratively with cross-functional teams in design, product, data science, operations, and research
- Industry experience building and productionizing Machine Learning models for Fraud Detection or Customer Support is a plus
- Industry experience building end-to-end Machine Learning infrastructure is a plus