Disney and Hulu's Recommendation Research team is seeking a RSDE(Research Software Develop Engineer) to conduct cutting-edge research work in the online video streaming recommendation area, tackling some of the most challenging and exciting machine learning problems.
The recommendation team analyzes and leverages petabytes of user and content data in order to serve the right content to the right users, and create the best personalized online video experience. While we stand firmly on statistical and mathematical foundations, we see great value in real world, creative and pragmatic solutions.
If you are someone who is seeking for opportunities building extraordinary online video recommendation engines, if you are someone who is proactive, inquisitive, and innovative in either of these domains, this is a phenomenal role for you!
WHAT YOU'LL DO
• Apply state-of-the-art machine learning techniques to real-world recommendation problems, such as relevance prediction, user modeling, learning to ranking, and natural language understanding
• Invent and fast iterate on novel solutions to challenging machine learning problems
• Develop scalable and efficient methods for large scale data analysis and model development
• Collaborate with program managers, and product managers and researchers in an open and creative environment
WHAT TO BRING
• MS or PhD in computer science, EE or other related discipline
• 2+ years of working experience on large scale machine learning, user behavior analysis in leading internet companies. Experience in personalization technology is highly preferred
• Familiarity with Java, Python, C/C++ or any other OOP language, familiar with tensorflow, pytorch or other machine learning platform
• Proven track record of thriving in a fast-paced, data-driven, collaborative and iterative applied research environment
• Outstanding track record in the areas of machine learning, data mining, or statistical modeling. Publications in renowned journals, conferences would be a big plus
• Excellent written and oral communication skills
Jobcode: Reference SBJ-g387qx-34-231-147-28-42 in your application.