About the Job
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting-edge Generative AI algorithms to solve real-world problems with significant impact? The Generative AI Innovation Center at AWS is a new strategic team that helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This team of strategists, data scientists, engineers, and solution architects works step-by-step with customers to build bespoke solutions that harness the power of generative AI.
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost-efficiently.
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for ML Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
Key Job Responsibilities
As an ML Data Scientist, you will:
- Collaborate with ML scientists 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 problems, aid in the implementation of generative AI solutions, and deliver briefing and deep dive sessions to 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.
Basic Qualifications
- Bachelor or Master's degree in Computer Science, Computer Engineering, or a related technical field plus several years of experience.
- Experience in 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 using Python and hands-on experience building models with deep learning frameworks like TensorFlow, Keras, PyTorch, or MXNet.
Preferred Qualifications
- Proven knowledge of Generative AI and hands-on experience building applications with large foundation models.
- Proven knowledge of the AWS platform and tools.
- Hands-on experience building ML solutions on AWS.
