Applied Scientist
Amazon
DESCRIPTIONAre you a scientist interested in pushing the state of the art in computer vision, ML, or LLMs? Are you an expert in text-to-text, text-to-image, image-to-image, or image-to-text models? 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, computer vision, ML and NLP algorithms. 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 technological problems that are cutting edge. Where technology does not exist, we will build it. Where it exists, we 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 #hitechKey job responsibilities
– Derive novel computer vision and ML models or LLMs/LMMs.
– Design and develop scalable ML models.
– Work with large datasets.
– Work with large GPU clusters.
– Work closely with software engineering teams to deploy your innovations.
– Publish your work at major conferences/journals.
– Mentor team members in the use of your AI models.
Barcelona
Sat, 31 Aug 2024 00:56:50 GMT
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