Principal Research Engineer in Recommendation System

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming

Job Description

We're looking for a principal researcher in recommendation who is comfortable working with multiple languages, frameworks, platforms and excited to participate in cutting-edge applied research in machine intelligence and machine learning applications. As a senior researcher, you’ll be responsible for formulating industrial problems into research questions and thus performing research to innovate solutions for personalization and content discovery. If you’re excited to work with a group of friendly and experienced machine learning researchers to build the machine intelligence to support high-performance, high-availability, scalable services, this is likely the team for you.

Responsibility

• Key contributor of continuous improvements of the personalized experiences in Hotstar. Boost our users engagement and retention by fully utilizing Disney & Hotstar 's catalog.
• Manage recommendation projects, define engineering roadmaps and drive the technical solutions.
• Gain deep insight of our product and metrics, discover and revise the objectives of personalization, and participate in the long-term plan of the personalization team. 
• Partner closely with the data analytics team, product team, and other teams to establish effective cross-team communications and cooperation.
• Design and build high-efficiency and high-quality recommendation systems through deep-learning algorithms. Monitor, maintain and improve the performance continuously over time. 
• Apply state-of-the-art algorithms to real-world problems in multiple scenarios, e.g on-site recommendation, off-site notification and internationalization.
• Apply state-of-the-art algorithms to real-world problems in multiple scenarios, e.g on-site recommendation, off-site notification and internationalization.
• Identify and abstract the key objectives, factors and processes of recommendation engine, enrich recommendation and machine learning platforms and infrastructures.
• Keep track of both industry and academic research trends in related areas, including but not limited to recommendation, machine learning and distributed computation. 

Qualifications

• 5+ industry experience of practical algorithm design and implementation in recommendation or machine learning related fields
• Ability and experiences to lead or drive engineering projects related to recommendation or machine-learning. 
• Strong understanding of recommendation models and other related machine learning techniques from both industry and academia. Abundant mathematics and statistics background.
• Extensive knowledge and hands-on experiences in big data processing frameworks such as Hive, Spark. Experiences in streaming-related computation such as Kafka, Flink or Spark streaming is a plus.
• Solid coding and engineering skills in Python/Java or other related programming languages . Rich experiences with deep-learning frameworks, such as Tensorflow.
• Logical thinker and quick learner with strong problem solving and analytical ability to apply your mathematical, algorithmic and other expertise to solve real problems.
• Passion for applied research, open to interdisciplinary work
• Strong communication skills, both in verbal and written English.