Overview

Can Alexa help anyone experience the music they enjoy? Even if they don’t know what they’d like to listen to in this moment? Or, if they know they want “Happy rock from the 90s”, can she help them find it?
Your machine learning leadership skills can help make that a reality on the Amazon Music team. We are seeking a Manager to lead a team of experts in the field of machine learning to break new ground in the world of understanding and classifying different forms of music, and create interactive experiences to help users find the music they are in the mood for. We work on machine learning problems for music classification, recommender systems, dialogue systems, NLP, and music information retrieval.
You’ll work in a collaborative environment where your team can pursue ambitious, long-term research, with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy their algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish research. You’ll see the work of your team directly improve the experience of Amazon Music customers on Alexa/Echo, mobile, and web.
The successful candidate will have a PhD in Computer Science with a strong focus on machine learning, or a related field, 5+ years of practical experience applying ML to solve complex problems in recommender systems, information retrieval, signal processing, NLP or dialogue systems, and 2+ years of practical experience managing one or more machine learning teams. Great if you have a passion for music, but this is not a requirement.
Responsibilities:
Lead a team that advances long-term, exploratory research projects in machine learning and related fields to create highly innovative customer experiences;
Develop and manage the long-term vision and portfolio of research initiatives for your team;
Manage the design, development and evaluation of highly innovative, scalable models and algorithms;
Lead experienced scientists as well as develop junior members from academia/industry to a successful career track in applied science;
Grow your team by hiring the best;
Project manage cross-functional projects;
Work with product and software engineering teams to manage the integration of successful models and algorithms in complex, real-time production systems at very large scale.

Company:

Amazon

Qualifications:

Basic Qualifications
PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent);
5+ years experience applying ML to solve complex problems for large-scale applications;
2+ years experience managing Machine Learning Scientists;
Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives;
Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes;
Experience hiring and leading experienced scientists as well as a successful record of developing junior members from academia/industry to a successful career track
Preferred Qualifications
PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent);
8+ years of practical experience applying ML to solve complex problems for applications handling gigabyte and terabyte size datasets;
Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval;
Track record of scientific publications in premier journals and conferences;
3+ years experience managing Machine Learning Scientists;
Skilled with Java, C++, or other programming language, as well as with R, MATLAB, Python or similar scripting language;
Professional experience in software development (software design and development life cycle);
Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives;
Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes;
Project management experience for working on cross-functional projects;
Proven achievements of developing and managing a long-term research vision and portfolio of research initiatives, with algorithms and models that have been successfully integrated in production systems;
Strong track record of hiring and leading experienced scientists as well as a successful record of developing junior members from academia/industry to a successful career track;
Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts.

Educational level:

Ph. D.

Level of experience (years):

Senior (5+ years of experience)

How to apply:

Please mention NLP People as a source when applying

https://us-amazon.icims.com/jobs/541817/head-of-machine-learning-research—nlp%252C-speech%252C-personalization/job?mode=job&iis=Job+Posting&iisn=LinkedIn.com&mobile=false&width=1279&height=1200&bga=true&needsRedirect=false&jan1offset=60&jun1offset=120

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About Amazon

Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon continues to grow and evolve as a world-class e-commerce platform.

Founded by Jeff Bezos, the Amazon.com website started in 1995 as a place to buy books because of the unique customer experience the Web could offer book lovers. Bezos believed that only the Internet could offer customers the convenience of browsing a selection of millions of book titles in a single sitting. During the first 30 days of business, Amazon fulfilled orders for customers in 50 states and 45 countries - all shipped from his Seattle-area garage.

Amazon's evolution from Web site to e-commerce partner to development platform is driven by the spirit of innovation that is part of the company's DNA. The world's brightest technology minds come to Amazon.com to research and develop technology that improv