Data Scientist, AWS Generative AI Innovation Center
hace 3 días
About the Role
Data Scientists capable of using generative AI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems are sought after by Amazon. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. Key responsibilities include collaborating with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges. Additionally, you will interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers, and guide customers on adoption patterns and paths to production.
Responsibilities
- Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges.
- Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers, and guide customers on adoption patterns and paths to production.
- 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
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train or fine-tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The Generative AI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.
Qualifications
- Bachelor's degree or Master's degree with several years of experience.
- Several years of experience building models for business applications.
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods, and/or machine learning.
- Experience in using Python and hands-on experience building models with deep learning frameworks like TensorFlow, Keras, PyTorch, or MXNet.
Preferred Qualifications
- PhD or Master's degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field.
- Practical experience in solving complex problems in an applied environment.
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