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Applied Scientist, Skill Builder, AWS Training…
- Amazon (Arlington, VA)
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Description
Are you fascinated by the power of Large Language Models (LLM) and Artificial Intelligence (AI) to transform the way we learn and interact with technology? Are you passionate about applying advanced machine learning (ML) techniques to solve complex challenges in the cloud learning space? If so, AWS Training & Certification (T&C) team has an exciting opportunity for you as an Applied Scientist.
At AWS T&C, we strive to be leaders in not only how we learn about the latest AI/ML development and AWS services, but also how the same technologies transform the way we learn about them. As an Applied Scientist, you will join a talented and collaborative team that is dedicated to driving innovation and delivering exceptional experiences in our Skill Builder platform for both new learners and seasoned developers. You will be a part of a global team that is focused on transforming how people learn. The position will interact with global leaders and teams across the globe as well as different business and technical organizations.
Join us at the AWS T&C Science Team and become a part of a global team that is redefining the future of cloud learning. With access to vast amounts of data, cutting-edge technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the ways how worldwide learners engage with our learning system and builders develop on our platform. Together, we will drive innovation, solve complex problems, and shape the future of future-generation cloud builders.
Please visit https://skillbuilder.awsto learn more.
Key job responsibilities
- Apply your expertise in LLM to design, develop, and implement scalable machine learning solutions that address challenges in discovery and engagement for our international audiences.
- Collaborate with cross-functional teams, including software engineers, data engineers, scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions.
- Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance operational performance and customer experiences across Skill Builder.
- Continuously explore and evaluate state-of-the-art techniques and methodologies to improve the accuracy and efficiency of AI/ML systems.
- Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact.
About the team
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.
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.
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.
Basic Qualifications
- Master's degree in computer science, computer engineering, or related field
- Experience programming in Java, C++, Python or related language
- Experience in building large scale search, personalization, computerized adaptive testing, browser/UI automation, and/or simulation systems.
Preferred Qualifications
- Have publications at top-tier peer-reviewed conferences or journals
- Experience implementing algorithms using both toolkits and self-developed code
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,400/year in our lowest geographic market up to $212,800/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.
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