Senior Machine Learning Engineer - User Listing Marketplace Intelligence

2 days ago

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Airbnb

WebsiteLinkedInAll Job Openings

travel accommodations • collaborative economy • hospitality

5001 - 10000 employees

Founded 2007

👥 B2C

🛍️ eCommerce

💰 Post-IPO Equity on 2020-12

Description

• The ULM-ML team supports host personalization products and provides data driven solutions to achieve superior host experience on Airbnb. • There is a huge opportunity to improve the Host and Guest experience by leveraging open source, third party, and home grown ML models. • As a senior engineer, you will partner closely with our data science, product partners, and other ML + data engineers on the team to execute on these opportunities in order to improve the Host and Guest product experience on Airbnb. • 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. • Prototype machine learning use cases for use in the product, and work with stakeholders to iterate on requirements. • 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. • Must have experience in both Natural Language Processing and Computer Vision. • 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, state-of-art NLP and CV algorithms) 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.

Benefits

• This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits. • The actual base pay is dependent upon many factors such as training, transferable skills, work experience, business needs and market demands. • Base pay range is subject to change and may be modified in the future.