Applied Scientist Ii, Alexa Sensitive Content

8 hours ago


Bengaluru, India ADCI - BLR 14 SEZ Full time

Master’s degree in Computer Science (Machine Learning, AI, Statistics, Mathematics, or equivalent)
- Experience programming in Java, C++, Python or related language
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives

Job summary
Alexa is the voice activated digital assistant powering devices like Amazon Echo, Echo Dot, Echo Show, and Fire TV, which are at the forefront of this latest technology wave. To preserve our customers’ experience and trust, the Alexa Sensitive Content Intelligence (ASCI) team creates policies and builds services and tools through Machine Learning techniques to detect and mitigate sensitive content across Alexa. We are looking for an experienced Applied Science Manager to build industry-leading technologies in attribute extraction and sensitive content detection across all languages and countries.

An Applied Scientist II will be working with a team of exceptional scientists to develop novel algorithms and modeling techniques to advance the state of the art in NLP related tasks. You will work in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. You will collaborate with and mentor other junior scientists to raise the bar of scientific research in Amazon. Your work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies.

You will be joining a select group of people making history producing one of the most highly rated products in Amazon's history, so if you are looking for a challenging and innovative role where you can solve important problems while growing as a leader, this may be the place for you.
A day in the life
You will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve our sensitive contents detection and mitigation. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership.
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.
Job responsibilities

You'll contribute to the science solution design, 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. You contribute directly to our growth by hiring smart and motivated Scientists to establish teams that can deliver swiftly and predictably, adjusting in an agile fashion to deliver what our customers need.
- PhD in Computer Science (Machine Learning, AI, Statistics, Mathematics, or equivalent)
- Extensive knowledge and practical experience in some of the following areas: machine learning, statistics, deep learning, NLP (Natural Language Processing), recommendation systems, dialogue systems or information retrieval; Computer Vision
- Peer reviewed scientific contributions in premier journals and conferences
- Experience with defining research and development practices in an applied environment
- Track record in technically leading, mentoring scientists
- Excellent written and verbal communication skills. Able to explain complex solutions in easy-to-understand terms.



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