Come work with other scientists and software developers in Alexa Smart Home to design and build the next generation of Smart Home experiences using the latest multimodal Large Language Models (LLMs) and Computer Vision.
We are evolving Alexa into an intelligent indispensable companion that automates daily routines simplifies interaction with appliances electronics and cameras and alerts when something unusual is detected. We are focused on making Alexa the user interface for the home from the simplest voice commands (turn on the lights turn down the heat) to use cases spanning home security home entertainment and the home environment. You can be part of a team delivering features that are highly anticipated by media and well received by our customers. And you will have the satisfaction of working on a product your friends and family can relate to and want to use every day.
Key job responsibilities
Develop new inference and training techniques to improve the performance of LLMs for Smart Home control and Automation
Solve hard problems in computer vision video summarization and video search
Develop robust techniques for synthetic data generation for training large models and maintaining model generalization
Mentoring junior scientists to improve their skills knowledge and their ability to get things done
About the team
We are a team of Scientists Machine Learning Engineers and Software Developers that work together to make Alexa more insightful and proactive through ambient intelligence with features like Alexa Hunches that automatically control Smart Home devices.
We are interdisciplinary and we act like it. We ask each other questions and value our different perspectives.
PhD or Masters degree and 4 years of CS CE ML or related field experience
Experience in patents or publications at toptier peerreviewed conferences or journals
1 years of building models for business application experience
Experience programming in Java C Python or related language
Experience in professional software development
Experience in stateoftheart deep learning models architecture design and deep learning training and optimization and model pruning
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.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees supervisors and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees supervisors and staff to ensure exceptional customer service; and follow all federal state and local laws and Company policies. Criminal history may have a direct adverse and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above as well as the abilities to adhere to company policies exercise sound judgment effectively manage stress and work safely and respectfully with others exhibit trustworthiness and professionalism and safeguard business operations and the Companys reputation. Pursuant to the Los Angeles County Fair Chance Ordinance we will consider for employment qualified applicants with arrest and conviction records.
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Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136000/year in our lowest geographic market up to $223400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon 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 This position will remain posted until filled. Applicants should apply via our internal or external career site.