Senior Machine Learning Engineering

Summary

Join Airbnb's Trust team as a Senior Machine Learning Engineer and make a difference in protecting our global community and platform from fraud. You will work with large-scale data, build and improve machine learning models for various use cases, collaborate with cross-functional partners, and develop and operate models at scale. A typical day involves tackling complex problems, driving engineering decisions, and quantifying impact. This role requires extensive experience in applied machine learning, strong programming skills, and familiarity with various technologies. The position is US-remote eligible, with occasional office work or offsites. Compensation includes a competitive salary, bonus, equity, benefits, and employee travel credits.

Requirements

• 5+ years of industry experience in applied Machine Learning, inclusive MS or  PhD in relevant fields
• 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

Responsibilities

• 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
• 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 machine learning models, drive engineering decisions, and quantify impact
• Work closely with other trust defense and platform teams to tackle the changing landscape of fraud attacks
• Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases
• Examples include: Anomaly detection models, ML models for continuous risk evaluation

Preferred Qualifications

Experience with the Trust and Risk domain is a plus

Benefits

This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits