Machine learning on news ranking is crucial for analyzing millions of articles everyday to deliver the most engaging high quality information in near-real-time while providing Personalized Discovery experience to our users.
Responsibilities
Machine Learning engineers are responsible for tackling complex problems to optimize the ranking and recommendation system (example: search ranking, collaborative filtering, personalized recommendation, diversification, and more)
- Plan and execute engineering development of state-of-the-art core-ranking system to provide a “Personalized Discovery” experience to millions of users
- Develop algorithms and model architecture to deepen understanding of article contents as well as user behaviors
- Collaborate with global cross-functional teams to support new product feature development
- Work closely with software engineers to enhance systems related to news features (articles, pages, channels, search, etc.) using Machine Learning technology, providing high quality user experience and increasing user engagement
- Proactively contribute to system improvements that result in direct user impact through innovation and creative thinking
Requirements
- 1+ years of experience in designing and implementing machine learning algorithms for online product and services (ideally related to ranking, recommendation, personalization etc) and applying them to real world problems (will consider research and internship)
- 3 years of software development experience in any programming languages (e.g. Java, C++, Python, Scala)
- MS, Ph.D or BS in computer science, mathematics, physics, machine learning, artificial intelligence, or other quantitative fields
- Ability to work with cross-functional teams globally with a “team player” mindset
Nice to haves
These aren’t required, but be sure to mention them in your application if you have them.
- Experience working as a software engineer and/or machine learning/AI engineer in a technology company
- Experience working as an Applied Scientist, Researcher, Data Scientist in relevant fields with hands-on software engineering experience
- Familiarity with one or more of the following Machine Learning libraries: Tensorflow, xgboost, Keras, PyTorch, scikit-learn, pandas, numpy, etc.
- Knowledge of developing and debugging in Java and Spring-boot
- Experience with Hadoop/Hive/Spark/AWS
- Solid Machine Learning background and deep understanding of certain domain of machine learning techniques, especially in natural language processing, recommendation systems, and/or computer visions
