Description 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 builds services and tools through Machine Learning techniques to implement our policies to detect and mitigate sensitive content in across Alexa. We are looking for an experienced Principal Applied Science to build industry-leading technologies in attribute extraction, annotation, and sensitive content detection and interpretation across all languages, modal, and countries. A Principal Applied Scientist will be a tech lead for a team of exceptional scientists to develop novel algorithms and modeling techniques to advance the state of the art in Artificial Intelligence (AI), Natural Language Understanding (NLU), Machine Learning (ML), Dialog Management, Automatic Speech Recognition (ASR), and Audio Signal Processing 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 scientists to raise the bar of scientific research in Amazon. Key job responsibilities A Principal Applied Scientist should have good understanding of NLP models (e.g. LSTM, LLMs, other transformer based models) or CV models (e.g. CNN, AlexNet, ResNet, GANs, ViT) where to apply them in different business cases. You leverage your exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience of building large-scale distributed systems to creating reliable, scalable, and high-performance products. In addition to technical depth, you must possess exceptional communication skills and understand how to influence key stakeholders. 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 for worldwide coverage. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, model development, and solution implementation. 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 team 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. Basic Qualifications · Master’s degree in Computer Science (Machine Learning, AI, Statistics, Mathematics, or equivalent) · 6+ years of experience in building machine learning models for business application especially applying NLP or Computer Vision to solve complex problems · Experience programming in Java, C++, Python or related language · Algorithm and model development experience for large-scale applications · Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives Preferred Qualifications · PhD in Computer Science (Machine Learning, AI, Statistics, Mathematics, or equivalent) · 10+ years of practical experience applying ML to solve complex problems · 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. 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. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.