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As an ML Engineer, you'll partner with technology and business teams to build solutions that surprise and delight our customers. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies.We’re looking for Engineers and Architects 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 responsibilities- Create and deliver reusable technical assets that help to accelerate the adoption of generative AI on AWS platformDiverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.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
Bachelor’s degree in computer science, engineering, mathematics or equivalentSeveral years of non-internship professional software development experience and experience coding in Python, R, Matlab, Java or other modern programming languageSeveral years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experienceProven knowledge of deep learning and experience using Python and frameworks such as Pytorch, TensorFlowSeveral years of relevant experience in developing and deploying large scale machine learning or deep learning models and/or systems into production, including batch and real-time data processing, model containerization, CI/CD pipelines, API development, model training and productionizing ML models
Masters or PhD degree in computer science, or related technical, math, or scientific fieldProven knowledge of Generative AI and hands-on experience of building applications with large foundation modelsExperiences related to AWS services such as SageMaker, EMR, S3, DynamoDB and EC2, hands-on experience of building ML solutions on AWSStrong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts
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