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    Applied Scientist - Santa Clara, United States - Amazon

    Amazon background
    Description


    Amazon is looking for an Applied Scientist to join our science team in the area of Speech and Natural Language Processing.

    Our organization develops the science that drives the cloud-based AI services of AWS


    Our mission is two-fold:
    empower developers with powerful AI tools and create delightful user experiences that solve real-world business problems.

    You'll have the opportunity to push the boundaries of machine learning by advancing techniques in automatic speech recognition, natural language understanding, and exciting areas like Generative AI and Large Language Models.


    As an Applied Scientist you will partner with talented scientists and engineers to design, train, test, and deploy machine learning models.

    You will contribute to innovative features, improve our services based on customer requirements and help maintain a highly scalable data and model management infrastructure that supports cutting-edge research.

    You will be responsible for translating business and engineering requirements into deliverables and software products.


    We are looking for candidates who thrive in an exciting, fast-paced environment and who have a strong personal interest in learning, researching, and creating new technologies with high customer impact.


    Prior domain knowledge in speech and natural language processing is strongly preferred; solid knowledge of fundamentals of statistics, machine learning, and deep learning is required.

    Candidates should possess strong software engineering skills and several years of industry experience.

    Amazon Bedrock team is part of Utility Computing (UC)

    About the team


    AWS Utility Computing (UC) provides product innovations - from foundational services such as Amazon's Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS's services and features apart in the industry.

    As a member of the UC organization, you'll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.

    Diverse Experiences

    AWS values diverse experiences.

    Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply.

    If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

    Why AWS?

    Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform.

    We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

    Inclusive Team Culture

    Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences.

    Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

    Mentorship & Career Growth

    We're continuously raising our performance bar as we strive to become Earth's Best Employer.

    That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

    Work/Life Balance

    We value work-life harmony.

    Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture.

    When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

    Hybrid Work

    We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face.

    Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S.

    Amazon offices.

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

    Santa Clara, CA, USA

    Basic Qualifications

    • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
    • Experience in patents or publications at toptier peerreviewed conferences or journals
    • Experience programming in Java, C++, Python or related language
    Preferred Qualifications

    • Experience in professional software development
    • 3+ years of building machine learning models or developing algorithms for business application experience
    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

    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 $222,200/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.

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