ML Engineer, Generative AI Innovation Center
2 settimane fa
The Generative AI Innovation Center at Amazon is seeking a highly skilled ML Engineer to join our team. As an ML Engineer, you will partner with technology and business teams to build innovative solutions that harness the power of generative AI.
You will work directly with customers to understand their business needs and develop bespoke solutions that address real-world challenges. Your expertise in deep learning and experience with Python and frameworks such as PyTorch and TensorFlow will be invaluable in designing and developing cutting-edge generative AI algorithms.
Key responsibilities include collaborating with ML scientists and engineers to research and develop new generative AI solutions, working across customer engagement to understand adoption patterns, and interacting with customers to understand their business problems and provide guidance on adoption patterns and paths for generative AI.
As a member of our team, you will have the opportunity to create and deliver reusable technical assets, best practice recommendations, and tutorials to help accelerate the adoption of generative AI on the AWS platform.
We are looking for a talented engineer who is passionate about generative AI and has a strong background in machine learning and deep learning. If you are a team player who is excited about the opportunity to work on innovative projects and make a real impact, we encourage you to apply.
RequirementsBachelor's degree in computer science, engineering, mathematics, or equivalent.
Several years of non-internship professional software development experience and experience coding in Python, R, Matlab, Java, or other modern programming languages.
Proven knowledge of deep learning and experience using Python and frameworks such as PyTorch and TensorFlow.
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 QualificationsMasters 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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