ML Engineer, Generative AI Innovation Center
4 settimane fa
DESCRIPTION
The 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, 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.
BASIC QUALIFICATIONS
- Bachelor'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.
- Several years of non-internship design or architecture (design patterns, reliability, and scaling) of new and existing systems experience.
- Proven knowledge of deep learning and experience using Python and frameworks such as Pytorch, 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 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.
- 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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