About the Job
Amazon launched the Generative AI Innovation Center (GenAIIC) in June 2023 to assist AWS customers in accelerating the use of generative AI for solving business and operational challenges, as well as fostering innovation. This team consists of strategists, data scientists, engineers, and solution architects collaborating with customers to develop bespoke solutions utilizing generative AI. We seek Data Scientists capable of employing GenAI and other techniques to design, promote, and implement state-of-the-art solutions for unprecedented problems. You will engage directly with customers, innovate in a dynamic environment, and contribute to transformative projects and technologies. Your responsibilities will include designing and conducting experiments, researching new algorithms, and discovering innovative methods to optimize risk, profitability, and customer experience.
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Key Responsibilities
- Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms to tackle real-world challenges.
- Engage with customers to understand their business problems, assist them in implementing generative AI solutions, and deliver comprehensive briefing and deep dive sessions.
- Create and present best practice recommendations, tutorials, blog posts, sample code, and presentations tailored for technical, business, and executive stakeholders.
- Provide feedback from customers and the market to Product and Engineering teams to help shape product direction.
About the Team
The Generative AI Innovation Center team guides customers in conceptualizing and determining the use cases that offer the most substantial value for their businesses. This includes selecting and training or fine-tuning appropriate models, navigating technical or business challenges, developing proof-of-concepts, and planning for large-scale solution launches while ensuring responsible and cost-effective application of generative AI.
Basic Qualifications
- Bachelor's degree or Master's degree with several years of relevant experience
- Extensive experience in building large scale machine learning or deep learning models
- Proficiency in data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab)
- Knowledge in areas such as algorithms and data structures, numerical optimization, data mining, parallel and distributed computing, high-performance computing, and neural deep learning methods
- Experience using Python and hands-on experience with deep learning frameworks like TensorFlow, Keras, PyTorch, or MXNet
- Strong communication skills across technical and non-technical audiences
Preferred Qualifications
- PhD or Master's degree in computer science, engineering, mathematics, operations research, or a highly quantitative field
- Practical experience in addressing complex problems in applied environments
- Hands-on experience with deep learning techniques (e.g., CNN, RNN, LSTM, Transformer)
- Previous experience in training and fine-tuning of Large Language Models (LLMs)
- Familiarity with AWS platform and tools
