Amazon Principal Applied Scientist Deep Science Systems & Services 

United States, California 

815785743

AWS AI/ML is looking for world class scientists and engineers to work on foundation models, large-scale representation learning, and distributed learning methods and systems. At AWS AI/ML you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and innovate on new representation learning solutions. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists.Large-scale foundation models have been the powerhouse in many of the recent advancements in computer vision, natural language processing, automatic speech recognition, recommendation systems, and time series modeling. Developing such models requires not only skillful modeling in individual modalities, but also understanding of how to synergistically combine them, and how to scale the modeling methods to learn with huge models and on large datasets. Join us to work as an integral part of a team that has diverse experiences in this space. We actively work on these areas: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

10+ years of relevant, broad research experience after PhD degree or equivalent.
Deep expertise in foundational models as well as knowledge of the latest trends in related areas in Machine Learning.
Proficiency in programming for algorithm and code reviews.
Strong core competency in building solutions
Track record of successful projects in algorithm design and product development.
Publications at top-tier peer-reviewed conferences or journals.
Strong prior experience with mentorship and/or management of senior scientists and engineers.

PhD in Computer Science, Machine Learning, Mathematics, or related quantitative discipline.
Expert level skills across many Machine Learning methodologies.
Published peer reviewed papers and journals at top rated academic venues.
Experience delivering complex end-to-end global ML solutions that run at very big scale.
Experience with access management and security solutions.
Effective verbal and written communication skills with non-technical and technical audiences.
Experience working with real-world data sets and building scalable models from big data.
Experience thinking strategically and with tactical execution.
Experience recruiting high caliber talent.