Data Scientist, GenAI Innovation Center

DescriptionAre you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center at AWS is a new strategic team that helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.We're looking for Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.Key job responsibilities

Collaborate with AI/ML scientists and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challengesInteract with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to productionCreate and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholderProvide customer and market feedback to Product and Engineering teams to help define product directionBasic Qualifications3+ years of experience building models for business applicationsExperience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learningExperience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNetBachelor's degree and 5 years of experience or Master's degree and 2 years of experiencePreferred Qualifications

PhD or Masters degree in computer science, engineering, mathematics, operations research, or in a highly quantitative fieldPractical experience in solving complex problems in an applied environmentHands on experience building models with deep learning frameworks like PyTorch, Tensorflow, or JAX

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