Senior Applied Scientist, GAI Innovation Center, AWS

In June 2023, Amazon inaugurated the Generative AI (GenAI) Innovation Center (GAIIC) to assist AWS customers in enhancing business innovation and success with Generative AI. Clients including Highspot, Lonely Planet, Ryanair, and Twilio are partnering with the GAI Innovation Center to explore the creation of generative solutions. GAIIC provides opportunities to innovate in a rapidly evolving organization that contributes to groundbreaking projects and technologies that are implemented on devices and in the cloud. As an applied scientist at GAIIC, you are skilled in constructing and developing advanced Generative AI-based solutions to address diverse client problems. You will be working with terabytes of text, images, and other data types to tackle real-world issues via Gen AI. You will be working closely with account teams and ML strategists to define the use case, and with other scientists and ML engineers on the team to design experiments, and discover new methods to deliver value to the client. The successful candidate will possess both technical and customer-facing skills that will allow them to be the technical "face" of AWS within our solution providers' ecosystem/environment as well as directly to end customers. You will be able to drive discussions with senior technical and management personnel within customers and partners. Inclusive Team Culture Here at AWS, we cherish our differences. We are dedicated to enhancing our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees across 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. Amazon's culture of inclusion is reinforced within our 14 Leadership Principles, which encourage team members to seek diverse perspectives, be curious and learn, and earn trust. Work/Life Balance Our team highly values a good work-life balance. It's not about the number of hours spent at home or at work, but about establishing a rhythm that energizes both aspects of your life. We believe achieving the right harmony between your personal and professional life is crucial for lifelong happiness and fulfillment. We offer flexible working hours and encourage you to find your own work-life balance. Mentorship & Career Growth Our team is committed to supporting new members. We comprise a broad array of experience levels and tenures, fostering an environment that values knowledge sharing and mentorship. Our senior members enjoy one-on-one mentorship and comprehensive, compassionate code reviews. We prioritize your career growth and aim to assign projects that will help each team member grow into a better-rounded engineer and allow them to handle more intricate tasks in the future. We are open to hiring candidates to work out of one of the following locations: Chicago, IL, USA | New York, NY, USA | San Francisco, CA, USA | Santa Clara, CA, USA | Seattle, WA, USA Basic Qualifications - 3+ years of experience building machine learning models for business applications - Proficiency in Java, C++, Python or related programming language - Familiarity with neural deep learning methods and machine learning Preferred Qualifications - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, etc. - Experience with large scale distributed systems such as Hadoop, Spark, etc. - PhD, or Master's degree and 6+ years of applied research experience Amazon is dedicated to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the grounds of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other legally protected status. We invite individuals with disabilities seeking accommodation to visit https://www.amazon.jobs/en/disability/us. In compliance with the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our compensation reflects labor costs across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographical market up to $260,000/year in our highest geographical market. Pay is determined by a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Depending on the position offered, equity, sign-on bonuses, 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.