Staff Machine Learning Engineer (Relevance and Personalization)

Join Airbnb's Relevance and Personalization team as a Staff Machine Learning Engineer. In this role, you will work on critical projects focused on developing end-to-end ranking algorithms and optimizing multiple business objectives. You will collaborate with cross-functional partners, work with large-scale data, and leverage cutting-edge AI technologies. The position offers a range of benefits, including paid volunteer time, health food and snacks, generous parental and family leave, learning and development opportunities, and an annual travel and experiences credit.

• Be a leader in the team working on critical, impactful projects with focus on developing end-to-end ranking algorithms and ecosystems for optimizing multiple critical business objectives.
• 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.
• Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
• 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields
• Experience with test driven development, familiar with A/B testing, incremental delivery and deployment
• 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)
• Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. neural networks/deep learning, optimization) and domains (eg. natural language processing, computer vision, personalization, search and recommendation, marketplace optimization, anomaly detection)
• Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive)
• Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills