Amazon launched the Generative AI Innovation Center (GenAIIC) in June 2023 to help AWS customers accelerate the use of generative AI to solve business and operational problems and promote innovation in their organizations. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. We’re looking for 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. 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. Emirati national is required.
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Key Job Responsibilities
As a Data Scientist, you will:
- 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 them implement generative AI solutions, deliver briefings and deep dive sessions, 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.
Requirements
- Bachelor's degree or Master's degree with several years of experience.
- Several years of experience building models for business applications.
- 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 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.
- Hands-on experience building models with deep learning frameworks like PyTorch, TensorFlow, or JAX.
- Prior experience in training and fine-tuning of Large Language Models (LLMs).
- Knowledge of AWS platform and tools.
Work Conditions
We value work-life harmony and strive for flexibility as part of our working culture. Achieving success at work should never come at the expense of sacrifices at home.
