Machine Learning Scientific Director | Netflix, Inc. | Los Gatos, CA
Engineering
Machine Learning Scientific Director
Product EngineeringLos Gatos, CA
The
Algorithms Engineering (AE) team owns the research, development and
innovation for the algorithms driving the Netflix product including
Personalization and Search. We are looking for an experienced machine
learning leader to join our team and become the technical point of
reference for a brilliant team of researchers and developers. In this
position, you will lead the way in research and development of the next
generation of algorithms to improve the experience for our more than 40
million members in over 40 countries. You will work on advanced machine
learning problems such as personalized learning to rank, row ordering
and selection, personalized search and similarity models. For more
details on the kind of problems we are working on, read this 2-part blog post by members of our team.
You
will need to exhibit strong leadership and communication skills. You
will lead and mentor researchers and engineers with years of experience.
However, no management of direct reports is expected. To be successful
in this role, you must have a strong machine learning/data mining
background, both theoretically and in practical applications. Your
day-to-day work will include project technical leadership, mentoring,
contribution to project discussions, internal and external
presentations, but also individual research and development. The exact
combination of the previous tasks will depend on your individual
background and strengths, but you should expect all of them to be part
of your leadership role.
This
is the ideal role for you if you are an experienced applied machine
learning researcher who, as a next step in your career, is looking to
have a huge impact on a product loved by millions of people across the
world.
MINIMUM JOB QUALIFICATIONS:
* At least ten years of postdoctoral research experience
*
Strong background on machine learning and data mining with a broad
understanding of unsupervised and supervised learning methods. You will
be expected to be proficient with methods such as Gradient Boosted
Decision Trees, Matrix Factorization, Kernel Methods, LDA, or
Multi-armed Bandits. You will also be expected to be familiar with newer
approaches such as Deep Learning or Non-parametric Bayesian methods
* Strong mathematical skills with knowledge of statistical methods
* Proven software development skills and experience
* Experience with traditional data storage platforms and distributed systems such as Hadoop.
* Great communication skills
* PhD in computer science, statistics or equivalent
PREFERRED JOB QUALIFICATIONS:
* Experience in Recommender Systems or Search
* Relevant publications in the field of Machine Learning and/or Search & Recommender Algorithms
* Experience with Cloud Computing platforms and large web-scale distributed systems
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