Senior ML Engineer, AWS Generative AI Innovation CenterThe Generative AI Innovation Center at AWS helps AWS customers accelerate the use of Generative AI and realize transformational business opportunities. This is a cross-functional team of ML scientists, engineers, architects, and strategists working step-by-step with customers to build bespoke solutions that harness the power of generative AI.
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 Collaborate with ML 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 the business problem, aid them in the implementation of generative AI solutions, deliver briefing and deep dive sessions to customers, and guide customers on adoption patterns and paths for generative AI.Create and deliver reusable technical assets that help to accelerate the adoption of generative AI on the AWS platform.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.About the team Generative AI Innovation Center is a program that pairs you with AWS science and strategy experts with deep experience in AI/ML and generative AI techniques to:
Imagine new applications of generative AI to address your needs.Identify new use cases based on business value.Integrate Generative AI into your existing applications and workflows.Diverse 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.
Minimum Qualifications Bachelor's degree in computer science or equivalent.Experience in professional, non-internship software development.Experience coding in Python, R, Matlab, Java, or other modern programming languages.Several 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.Experience contributing to the architecture and design (architecture, design patterns, reliability, and scaling) of new and current systems.Preferred Qualifications Masters or PhD degree in computer science, or related technical, math, or scientific field.Proven knowledge of deep learning and experience using Python and frameworks such as Pytorch, TensorFlow.Proven knowledge of Generative AI and hands-on experience building applications with large foundation models.Experience related to AWS services such as SageMaker, EMR, S3, DynamoDB, and EC2, with hands-on experience building ML solutions on AWS.Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts.Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify, and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use, and transfer the personal data of our candidates.
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