Data Scientist, GenAI Innovation Center
3 weeks ago
Description
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 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.
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and 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 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 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
Collaborate with AI/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 problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer 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 stakeholder
Provide customer and market feedback to Product and Engineering teams to help define product direction
Basic Qualifications
3+ 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, MXNet
Bachelor's degree and 5 years of experience or Master's degree and 2 years of experience
Preferred Qualifications
PhD or Masters 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
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