Machine Learning Engineer, Generative AI Innovation Center
1 settimana fa
We are seeking a highly skilled Machine Learning Engineer to join our Generative AI Innovation Center at Amazon. As an ML Engineer, you will play a key role in helping our customers accelerate the use of Generative AI and realize transformational business opportunities.
Key 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, help and 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.
We are 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. The ideal candidate will have:
- Bachelor's degree in computer science, engineering, mathematics or equivalent.
- Several years of non-internship professional software development experience.
- Several years of non-internship design or architecture (design patterns, reliability, and scaling) of new and existing systems experience.
- 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.
- Proven knowledge of deep learning and experience using Python and frameworks such as Pytorch, TensorFlow.
The following qualifications are highly desirable:
- Masters or PhD degree in computer science, or related technical, math, or scientific field.
- Proven knowledge of Generative AI and hands-on experience of building applications with large foundation models.
- Experiences related to AWS services such as SageMaker, EMR, S3, DynamoDB and EC2, hands-on experience of building ML solutions on AWS.
- Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts.
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