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Description

Are you a scientist interested in pushing the state of the art in LLMs, ML or Computer Vision forward? Are you interested in working on ground-breaking research projects that will lead to great products and scientific publications? Do you wish you had access to large datasets? Answer yes to any of these questions and you’ll fit right in here at Amazon.

We are looking for a hands-on researcher, who wants to derive, implement, and test the next generation of Generative AI algorithms (either LLMs, Diffusion Models, auto-regressors, VAEs, or other generative models). The research we do is innovative, multidisciplinary, and far-reaching. We aim to define, deploy, and publish cutting edge research. In order to achieve our vision, we think big and tackle technology problems that are cutting edge. Where technology does not exist, we will build it. Where it exists we will need to modify it to make it work at Amazon scale. We need members who are passionate and willing to learn.

“Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.”

Please visit https://www.amazon.science for more information

#hltech #hitech

Key job responsibilities

• Derive novel ML or Computer Vision or LLMs and NLP algorithms

• Design and develop scalable ML solutions

• Work with very large datasets

• Work closely with software engineering teams and Product Managers to deploy your innovations

• Publish your work at major conferences/journals.

• Mentor team members in the use of your Generative AI and LLMs.

About the team

We are a tight-knit group that shares our experiences and help each other succeed. We believe in team work. We love hard problems and like to move fast in a growing and changing environment. We use data to guide our decisions and we always push the technology and process boundaries of what is feasible on behalf of our customers. If that sounds like an environment you like, join us.

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

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

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

• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• PhD

• PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field

• 4+ years of building machine learning models or developing algorithms for business application experience

• Experience with generative deep learning models like LLMs, Diffusion Models, Normalizing Flows, GANs, VAEs, or autoregressive

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