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.

Requirements

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, high volume data pipelines, efficient algorithms, models)
Experience with test driven development, familiar with A/B testing, incremental delivery and deployment.
Experience with the Trust and Risk domain is a plus.

Benefits

The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands.
This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Machine Learningdata engineeringprogrammingfeature engineeringgradient boosted treesneural networksnatural language processingcomputer visionanomaly detectionA/B testing

Soft Skills

collaborationcommunicationprioritizationproblem-solvingcross-functional teamwork

Certifications

MS in relevant fieldsPhD in relevant fields