Senior Software Engineer - Machine Learning Infrastructure
- Los Gatos, California
- Data Engineering and Infrastructure
Netflix is driven by data and algorithms (along with tons of great TV shows and movies). If you are in the engineering, data, and / or machine learning fields, this is an amazing place to be.
We're a team of engineers with diverse skills who envision, develop, and manage the systems and workflows that enable Netflix Data Scientists to focus more on modeling and less on engineering. We're solving problems like:
∙ What is the best way to take a prototype in R or Python and move it into ongoing production use at scale?
∙ How can we help ML practitioners reproduce their research and be more collaborative?
∙ How do we build flexible pipelines that can rapidly evolve to handle new technologies and modeling approaches?
∙ How can we streamline feature engineering, such that the underlying data is easily and efficiently extracted reusable across analyses?
This is just the tip of the iceberg, though. Our long term vision is to also enable non-data scientists to solve problems using ML.
Given Netflix’s rare combination of an exceptional team of data scientists, a lot of data, a sophisticated data engineering ecosystem, and a company-wide appreciation for the benefits of machine learning, a huge opportunity awaits.
Applied ML at scale is a new field, so chances are, you won't have years and years of experience doing it. If you're passionate about combining your talents with ours to tame this frontier, we'd like to hear from you. You're likely to make us better as a team if you possess one of these talents:
∙ Enabling ML - you've built some infrastructure for it
∙ Practicing ML - you've developed and deployed your own models
∙ Exceptional engineering skills - ideally in Python, or a similar language
∙ Developing systems - you've built meaningful pieces of infrastructure in a cloud computing environment. Bonus if those were data processing systems or distributed systems.
Practically no one possesses all of these, so you will certainly have the chance to develop them on this team.
For a much deeper dive into this team and role, please check out this Machine Learning Infrastructure team write-up.