Machine Learning Engineer, Generative AI Innovation Center

1 settimana fa


Milano, Lombardia, Italia Amazon A tempo pieno
About the Role

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 building cutting-edge generative AI solutions that surprise and delight our customers.

Key Responsibilities
  • Collaborate with ML scientists and engineers to research, design, and develop innovative generative AI algorithms to address real-world challenges.
  • Work across customer engagement to understand adoption patterns for generative AI and rapidly share them across teams and leadership.
  • Interact with customers directly to understand business problems, help and aid them in implementing 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 accelerate the adoption of generative AI on the AWS platform.
  • Provide customer and market feedback to Product and Engineering teams to help define product direction.
Requirements
  • 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 experience of new and existing systems.
  • 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.
Preferred Qualifications
  • 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.
  • Experience 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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