Description

　　At AWS, we use Artificial Intelligence to be able to identify every need of a customer across all AWS services before they have to tell us about it and help customers adopt best practices while architecting on the cloud. We are looking for Machine Learning Scientists / Applied Scientists / ML Scientists with unfettered curiosity and drive to help build “best in the world” experience that customers will love!

　　You will have an opportunity to lead, invent, and design tech that will directly impact every customer across all AWS services. We are building industry-leading technology that cuts across a wide range of ML techniques from Natural Language Processing to Deep Learning and Generative Artificial Intelligence. You will be a key driver in taking something from an idea to an experiment to a prototype and finally to a live production system.

　　Our team packs a punch with principal level product, science, engineering, and leadership talent. We are a results focused team and you have the opportunity to lead and establish a culture for the big things to come. We combine the culture of a startup, the innovation and creativity of a R&D Lab, the work-life balance of a mature organization, and technical challenges at the scale of AWS. We offer a playground of opportunities for builders to build, have fun, and make history!

　　Key job responsibilities

　　Deliver real world production systems at AWS scale.

　　Work closely with the business to understand the problem space, identify the opportunities and formulate the problems.

　　Use machine learning, data mining, statistical techniques, Generative AI and others to create actionable, meaningful, and scalable solutions for the business problems.

　　Analyze and extract relevant information from large amounts of data and derive useful insights.

　　Work with software engineering teams to deliver production systems with your ML models

　　Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation

　　A day in the life

　　About the team

　　Inclusive Team Culture

　　Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.

　　Work/Life Balance

　　Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

　　Mentorship & Career Growth

　　Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.

　　We are open to hiring candidates to work out of one of the following locations:

　　Bellevue, WA, USA | Seattle, WA, USA

　　Basic Qualifications

　　3+ years of building machine learning models for business application experience

　　PhD, or Master's degree and 6+ years of applied research experience

　　Knowledge of programming languages such as C/C++, Python, Java or Perl

　　Experience programming in Java, C++, Python or related language

　　Experience with neural deep learning methods and machine learning

　　Preferred Qualifications

　　Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalabilityAmazon 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 $136,000/year in our lowest geographic market up to $260,000/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. Applicants should apply via our internal or external career site.