Voice-driven AI experiences are finally becoming a reality and Amazon’s Alexa voice cloud service and Echo devices are at the forefront of this latest technology wave. We deliver world-class products on aggressive schedules that are used every day, by people you know, in and about their homes. At the same time, we obsess about customer trust and ensure that we build products in a manner that maintains our high bar for customer privacy. We are looking for a passionate and talented Applied Scientist with experience in delivering production systems based on innovative research. This is a unique opportunity to play a key role in an exciting, fast growing business. You will be working on one of the world's most cutting edge customer experience and technology.
A day in the life
You will be researching algorithm and runing experiments to test scientific propsoal/solutions to improve our sensitive contents detection and mitigation. This will involve collaobration with partener teams including enginering, PMs, data annotators, and other scientitists to discuss data quality, policy, model development, performance evaluation.
About the hiring group
The mission of the Alexa Sensitive Content Intelligence (ASCI) team is to (1) minimize negative surprises to customers caused by sensitive content, (2) detect and prevent potential brand-damaging interactions, and (3) build customer trust through appropriate interactions on sensitive topics.
The term “sensitive content” includes within its scope a wide range of categories of content such as offensive content (e.g., hate speech, racist speech), profanity, content that is suitable only for certain age groups, politically polarizing content, and religiously polarizing content. The term “content” refers to any material that is exposed to customers by Alexa (including both 1P and 3P experiences) and includes text, speech, audio and video.
You'll design and run experiments, research new algorithms, and find new ways of optimizing customer experience. Besides theoretical analysis and innovation, you will work closely with talented engineers and ML scientists to put your algorithms and models into practice. Your work will directly impact the trust customers place in Alexa, globally.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
· Graduate degree in Computer Science (Machine Learning, AI, Statistics, or equivalent);
· 2+ years of practical experience applying ML to solve complex problems;
· Algorithm and model development experience for large-scale applications;
· Experience using Java, C++, or other programming language, as well as with R, MATLAB, Python or similar scripting language;
· Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
· PhD in Computer Science (Machine Learning, AI, Statistics, Mathematics, or equivalent);
· 3+ years of practical experience applying ML to solve complex problems;
· Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, deep learning, Natural Language Processing, recommendation systems, dialogue systems, information retrieval;
· Significant peer reviewed scientific contributions in premier journals and conferences;
· Expert in more than one more major programming languages (C++, Java, or similar) and at least one scripting language (Perl, Python, or similar);
· Proven track record of production achievements, handling gigabyte and terabyte size datasets;
· Strong fundamentals in problem solving, algorithm design and complexity analysis;
· Strong personal interest in learning, researching, and creating new technologies with high customer impact;
· Experience with defining research and development practices in an applied environment;
· Proven track record in technically leading and mentoring scientists;
· Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.