Responsibilities
Machine Learning Tech Leads are responsible to lead teams to tackle complex problems related to recommendation and optimization (search ranking, collaborative filtering, personalized recommendation, diversification, and more) and make a company-wide impact
- Play a critical role in setting the direction and goals for a global machine learning team, in terms of project impact, core-ranking system design, and machine learning excellence.
- Plan and execute engineering development of state-of-the-art core-ranking system to provide Personalized Discovery experience to millions of users around the world.
- Collaborate closely with Engineering and Product Leadership and global cross-functional teams to develop global product.
- Be a go-to person for software engineers to enhance systems related to news features (articles, pages, channels, search, etc) by developing complex algorithm and model architecture which will deepen the understanding of article contents as well as user behaviors to deliver high quality user experience and increase user engagement.
- Initiate and lead mid to large size projects.
- Mentor and coach other ML engineers in Japan and other regional offices.
Requirements
- Rich experience in hands-on developing the prediction, optimization, or other relevant systems for the online web service and products (e.g content recommendation, online advertisement, search optimization, etc).
- Experience in making company-wide business impact through machine learning, deep learning, or mathematical optimization (e.g achieving increase user’s time-spent in the service, etc).
- Familiar with architecture and implementation mechanism of at least one mainstream machine learning programming framework (TensorFlow/Pytorch/MXNet/etc).
- Initiate and lead mid to large size projects.
- Experience of leading and mentoring engineers.
- BS degree or above in Computer Science, Computer Engineering, Science (physics or mathematics) or other relevant majors
Nice to haves
These aren’t required, but be sure to mention them in your application if you have them.
- Familiarity with several of the following ML 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/Flink/AWS
