Senior Applied Scientist, Generative Artificial Intelligence (AI) Innovation Center
Job ID: 2840063 | Amazon Web Services Japan
The AWS Sales, Marketing, and Global Services (SMGS) team is responsible for driving revenue, adoption, and growth from small- and mid-market accounts to enterprise-level customers, including the public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success.
The Generative Artificial Intelligence (AI) Innovation Center team at AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies leveraging cutting-edge generative AI algorithms. As an Applied Scientist, you'll partner with technology and business teams to build solutions that surprise and delight our customers. We're looking for Applied Scientists capable of using generative AI and other ML techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
Key Job ResponsibilitiesCollaborate with scientists and engineers to research, design, and develop cutting-edge generative AI algorithms to address real-world challenges.Work across customer engagement to understand what adoption patterns for generative AI are working and rapidly share them across teams and leadership.Interact with customers directly to understand their business problems, aid them in implementing generative AI solutions, and deliver briefing and deep dive sessions.Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders.Provide customer and market feedback to Product and Engineering teams to help define product direction.BASIC QUALIFICATIONS5+ years of building machine learning models or developing algorithms for business applications.Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field.Knowledge of programming languages such as C/C++, Python, Java, or Perl.Proven knowledge of deep learning and experience hosting and deploying ML solutions (e.g., for training, tuning, and inferences).PREFERRED QUALIFICATIONSPhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field.Working knowledge of generative AI and hands-on experience in prompt engineering, deploying, and hosting Large Foundational Models.Hands-on experience building models with deep learning frameworks like TensorFlow, PyTorch, or MXNet.
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