Netflix is the world's first global internet television network, known for its personalization technologies. This year, Netflix will invest $6 billion in content and will create over 1000 hours of original content with great Hollywood talents like Kevin Spacey, Angelina Jolie and Martin Scorsese. The Netflix service delights more than 100 millions of members around the world with original movies and TV shows like "13 Reasons Why" and "Stranger Things", including reboot of old favorites like "Arrested Development" and "Gilmore Girls."
The Recommendations team develops algorithms and builds the recommendation systems that drive personalization to over 100 million of members across the globe, connecting our members and helping them discover great story telling on Netflix.
Here are some examples of the types of things we work on:
• Design & develop the next generation of web services that serve video recommendations
• Build large-scale distributed computation on Spark for producing targeting scores and predictions
• Innovate on personalization algorithm through A/B testing
• Provide accessibility to scores to other clients like Homepage, Consumer Science & Messaging
• Construct visualization that provides insights to recommendation data
Who We Are Looking For
You are an accomplished and passionate software engineer. You shine in a high-performance culture.
You want to engineer scalable and resilient Recommendation Systems. You’re excited by collaborating with product managers, UI engineers, data analysts and research engineers across product organizations to innovate personalization through A/B testing. You want to impact large-scale pipelines and systems that process terabytes of data. You exhibit leadership skills and want to drive technical direction for next generation systems that generate the demand of our next big original series.
We're looking for someone who has most of the following and is willing to learn the rest on the job as needed: