- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience building machine learning models or developing algorithms for business application
AWS AI is looking for passionate, talented, and inventive Applied Scientists with a strong machine learning background to help build industry-leading AI systems. As an Applied Scientist at AWS, you will be at the forefront of developing cutting-edge language technology, leveraging your strong machine learning background to push the boundaries of Natural Language Processing (NLP), Generative AI, and Large Language Models (LLMs). Your role will involve working on innovative projects that encompass language understanding, Retrieval-Augmented Generation (RAG), semantic parsing, responsible AI, and agentic workflow. You will collaborate with internationally recognized experts to develop novel algorithms and modeling techniques, directly impacting millions of customers through AWS products and services while contributing to the wider research community.
In this dynamic and entrepreneurial environment, you will have the opportunity to work with Amazon's vast array of text and structured data sources, as well as access to large-scale computing resources to accelerate advancements in language understanding. You will conduct groundbreaking research, influence the science roadmap, and shape the direction of the team. Your work will involve building and deploying state-of-the-art machine learning algorithms and systems, creating prototypes, and exploring conceptually new solutions. This role offers the chance to interact closely with customers and the academic community, publish your work in top-tier conferences and journals, and be at the heart of AWS's growing and exciting AI focus area.
Key job responsibilities
- Develop novel algorithms and modeling techniques in Natural Language Processing (NLP), Generative AI, Large Language Models (LLM), Natural Language Understanding (NLU), and Agentic workflows.
- Conduct innovative research and influence the science roadmap and direction of the team.
- Collaborate with internationally recognized experts to advance human language technology.
- Apply rigorous research methods to respond to large-scale NLP needs with efficient and scalable solutions.
- Leverage Amazon's vast data sources and large-scale computing resources to accelerate advances in language understanding.
- Contribute to the wider research community through publications in top-tier conferences and journals.
About the team
Amazon Q Apps, an Amazon Q Business capability empowers organizational users to quickly turn their ideas into apps, all in a single step from their conversation with Amazon Q Business or by describing the app that they want to build in their own words. With Amazon Q Apps, users can effortlessly build, share, and customize apps on enterprise data to streamline tasks and boost individual and team productivity. Users can also publish apps to the admin-managed library and share them with their coworkers. Amazon Q Apps inherit user permissions, access controls, and enterprise guardrails from Amazon Q Business for secure sharing and adherence to data governance policies.
Amazon Q Apps enhances business user experience and collaboration with new and improved capabilities. Customers can now bring the power of Amazon Q Apps into their tools of choice and application environment through APIs that seamlessly allow creating and consuming Amazon Q Apps outputs. App creators can now review the original app creation prompt to refine and improve new app versions without starting from scratch, as well as to pick data sources to improve output quality.
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.
- Experience using Unix/Linux
- 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 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 $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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
