Job summaryAs an Applied Scientist, you will take ownership of the technical roadmap and delivery of real-time, scalable machine learning models influencing ad selection, relevance and ranking models. You will work with other Applied Scientists and Machine Learning Engineers to experiment and innovate quickly with a diverse set of models, features and techniques in a high-volume, low-latency environment. Our workflows scan billions of documents, with milliseconds of latency budget while ensuring high relevance of retrieved items. So the level of quality and reliability is critically important.As a Applied Scientist on this team, you will:
- Build machine learning models that can scale to our run-time requirements.
- Run A/B experiments, gather data, and perform statistical analysis.
- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
- Research new and innovative machine learning approaches.
- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals
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